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37th NeurIPS 2023: New Orleans, LA, USA
- Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, Sergey Levine:
Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023. 2023 - Michael Bereket, Theofanis Karaletsos:
Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder. - Lucy Xiaoyang Shi, Yunfan Jiang, Jake Grigsby, Linxi Fan, Yuke Zhu:
Cross-Episodic Curriculum for Transformer Agents. - Xiang Li, Chung-Ching Lin, Yinpeng Chen, Zicheng Liu, Jinglu Wang, Rita Singh, Bhiksha Raj:
PaintSeg: Painting Pixels for Training-free Segmentation. - Yiren Jian, Chongyang Gao, Soroush Vosoughi:
Bootstrapping Vision-Language Learning with Decoupled Language Pre-training. - Yunzhang Zhu, Renxiong Liu:
Path following algorithms for 𝓁2-regularized M-estimation with approximation guarantee. - Yuhan Ding, Fukun Yin, Jiayuan Fan, Hui Li, Xin Chen, Wen Liu, Chongshan Lu, Gang Yu, Tao Chen:
PDF: Point Diffusion Implicit Function for Large-scale Scene Neural Representation. - Ruida Zhou, Tao Liu, Min Cheng, Dileep Kalathil, P. R. Kumar, Chao Tian:
Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation. - Rui M. Castro, Fredrik Hellström, Tim van Erven:
Adaptive Selective Sampling for Online Prediction with Experts. - Mathias Lechner, Lianhao Yin, Tim Seyde, Tsun-Hsuan Johnson Wang, Wei Xiao, Ramin M. Hasani, Joshua Rountree, Daniela Rus:
Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning. - Xiaolei Ru, Xinya Zhang, Zijia Liu, Jack Murdoch Moore, Gang Yan:
Attentive Transfer Entropy to Exploit Transient Emergence of Coupling Effect. - Thad Starner, Sean Forbes, Matthew So, David Martin, Rohit Sridhar, Gururaj Deshpande, Sam S. Sepah, Sahir Shahryar, Khushi Bhardwaj, Tyler Kwok, Daksh Sehgal, Saad Hassan, Bill Neubauer, Sofia Anandi Vempala, Alec Tan, Jocelyn Heath, Unnathi Kumar, Priyanka Mosur, Tavenner Hall, Rajandeep Singh, Christopher Cui, Glenn Cameron, Sohier Dane, Garrett Tanzer:
PopSign ASL v1.0: An Isolated American Sign Language Dataset Collected via Smartphones. - Jan Schuchardt, Yan Scholten, Stephan Günnemann:
(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More. - Zhaoying Pan, Daniel Geng, Andrew Owens:
Self-Supervised Motion Magnification by Backpropagating Through Optical Flow. - Xinrui Chen, Yizhi Wang, Renao Yan, Yiqing Liu, Tian Guan, Yonghong He:
TexQ: Zero-shot Network Quantization with Texture Feature Distribution Calibration. - Giannis Daras, Kulin Shah, Yuval Dagan, Aravind Gollakota, Alex Dimakis, Adam R. Klivans:
Ambient Diffusion: Learning Clean Distributions from Corrupted Data. - Martín Bertrán, Shuai Tang, Aaron Roth, Michael Kearns, Jamie Morgenstern, Steven Wu:
Scalable Membership Inference Attacks via Quantile Regression. - Qiyao Huang, Yingyue Zhang, Zhihong Zhang, Edwin R. Hancock:
ESSEN: Improving Evolution State Estimation for Temporal Networks using Von Neumann Entropy. - Hui Guo, Boyu Wang, Grace Yi:
Label Correction of Crowdsourced Noisy Annotations with an Instance-Dependent Noise Transition Model. - Mineui Hong, Minjae Kang, Songhwai Oh:
Diffused Task-Agnostic Milestone Planner. - Po-han Li, Sravan Kumar Ankireddy, Ruihan Philip Zhao, Hossein Nourkhiz Mahjoub, Ehsan Moradi-Pari, Ufuk Topcu, Sandeep Chinchali, Hyeji Kim:
Task-aware Distributed Source Coding under Dynamic Bandwidth. - Sheikh Md Shakeel Hassan, Arthur Feeney, Akash Dhruv, Jihoon Kim, Youngjoon Suh, Jaiyoung Ryu, Yoonjin Won, Aparna Chandramowlishwaran:
BubbleML: A Multiphase Multiphysics Dataset and Benchmarks for Machine Learning. - Zhuo Chen, Laker Newhouse, Eddie Chen, Di Luo, Marin Soljacic:
ANTN: Bridging Autoregressive Neural Networks and Tensor Networks for Quantum Many-Body Simulation. - Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash:
Causal Effect Identification in Uncertain Causal Networks. - Jia Gu, Caizhi Tang, Han Yan, Qing Cui, Longfei Li, Jun Zhou:
FAST: a Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation. - Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova:
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond. - Yuxuan Song, Jingjing Gong, Minkai Xu, Ziyao Cao, Yanyan Lan, Stefano Ermon, Hao Zhou, Wei-Ying Ma:
Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation. - Seunghyuk Cho, Juyong Lee, Dongwoo Kim:
Hyperbolic VAE via Latent Gaussian Distributions. - Kai Yan, Alexander G. Schwing, Yu-Xiong Wang:
A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories. - Zhenyi Wang, Li Shen, Tongliang Liu, Tiehang Duan, Yanjun Zhu, Donglin Zhan, David S. Doermann, Mingchen Gao:
Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training. - David Skrill, Samuel Norman-Haignere:
Large language models transition from integrating across position-yoked, exponential windows to structure-yoked, power-law windows. - Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Tingfan Wu, Jay Vakil, Pieter Abbeel, Jitendra Malik, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier:
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? - Jangwon Kim, Hangyeol Kim, Jiwook Kang, Jongchan Baek, Soohee Han:
Belief Projection-Based Reinforcement Learning for Environments with Delayed Feedback. - Amur Ghose, Apurv Gupta, Yaoliang Yu, Pascal Poupart:
Batchnorm Allows Unsupervised Radial Attacks. - Yichao Cao, Qingfei Tang, Xiu Su, Song Chen, Shan You, Xiaobo Lu, Chang Xu:
Detecting Any Human-Object Interaction Relationship: Universal HOI Detector with Spatial Prompt Learning on Foundation Models. - Alex Damian, Eshaan Nichani, Rong Ge, Jason D. Lee:
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models. - Alexander G. Reisach, Myriam Tami, Christof Seiler, Antoine Chambaz, Sebastian Weichwald:
A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models. - Anastasia Batsheva, Andrei Chertkov, Gleb V. Ryzhakov, Ivan V. Oseledets:
PROTES: Probabilistic Optimization with Tensor Sampling. - Junqi Gao, Biqing Qi, Yao Li, Zhichang Guo, Dong Li, Yuming Xing, Dazhi Zhang:
Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability. - Jeroen Berrevoets, Daniel Jarrett, Alex J. Chan, Mihaela van der Schaar:
AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems. - Ziniu Hu, Ahmet Iscen, Chen Sun, Kai-Wei Chang, Yizhou Sun, David Ross, Cordelia Schmid, Alireza Fathi:
AVIS: Autonomous Visual Information Seeking with Large Language Model Agent. - Prasenjit Dey, Srujana Merugu, Sivaramakrishnan R. Kaveri:
Conformal Prediction Sets for Ordinal Classification. - Shivam Gupta, Jasper C. H. Lee, Eric Price, Paul Valiant:
Minimax-Optimal Location Estimation. - Aditya Bhaskara, Sepideh Mahabadi, Ali Vakilian:
Tight Bounds for Volumetric Spanners and Applications. - Mohammad Mahdi Kamani, Yuhang Yao, Hanjia Lyu, Zhongwei Cheng, Lin Chen, Liangju Li, Carlee Joe-Wong, Jiebo Luo:
Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking. - Pingsheng Li, Jonathan Cornford, Arna Ghosh, Blake A. Richards:
Learning better with Dale's Law: A Spectral Perspective. - Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel. - Khashayar Gatmiry, Zakaria Mhammedi:
Projection-Free Online Convex Optimization via Efficient Newton Iterations. - Yue Wu, Yewen Fan, Paul Pu Liang, Amos Azaria, Yuanzhi Li, Tom M. Mitchell:
Read and Reap the Rewards: Learning to Play Atari with the Help of Instruction Manuals. - Kaiyue Wen, Zhiyuan Li, Tengyu Ma:
Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization. - Nikhil Vyas, Alexander B. Atanasov, Blake Bordelon, Depen Morwani, Sabarish Sainathan, Cengiz Pehlevan:
Feature-Learning Networks Are Consistent Across Widths At Realistic Scales. - Michele Garibbo, Maxime Robeyns, Laurence Aitchison:
Taylor TD-learning. - Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis:
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. - Nicholas Rittler, Kamalika Chaudhuri:
Agnostic Multi-Group Active Learning. - Jie Xu, Shuo Chen, Yazhou Ren, Xiaoshuang Shi, Hengtao Shen, Gang Niu, Xiaofeng Zhu:
Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration. - Mingli Zhu, Shaokui Wei, Hongyuan Zha, Baoyuan Wu:
Neural Polarizer: A Lightweight and Effective Backdoor Defense via Purifying Poisoned Features. - Dami Choi, Yonadav Shavit, David Kristjanson Duvenaud:
Tools for Verifying Neural Models' Training Data. - Yuchuan Tian, Hanting Chen, Tianyu Guo, Chao Xu, Yunhe Wang:
Towards Higher Ranks via Adversarial Weight Pruning. - Zeke Xie, Zhiqiang Xu, Jingzhao Zhang, Issei Sato, Masashi Sugiyama:
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective. - Yulhwa Kim, Dongwon Jo, Hyesung Jeon, Taesu Kim, Daehyun Ahn, Hyungjun Kim, Jae-Joon Kim:
Leveraging Early-Stage Robustness in Diffusion Models for Efficient and High-Quality Image Synthesis. - Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng:
Adversarial Model for Offline Reinforcement Learning. - Man Zhou, Naishan Zheng, Yuan Xu, Chun-Le Guo, Chongyi Li:
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function. - Andrew K. Lampinen, Stephanie C. Y. Chan, Ishita Dasgupta, Andrew J. Nam, Jane X. Wang:
Passive learning of active causal strategies in agents and language models. - Wenjing Yan, Xuanyu Cao:
Zero-Regret Performative Prediction Under Inequality Constraints. - Yichen Xie, Mingyu Ding, Masayoshi Tomizuka, Wei Zhan:
Towards Free Data Selection with General-Purpose Models. - Junyi Li, Feihu Huang, Heng Huang:
Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems. - Jun-Yi Hang, Min-Ling Zhang:
Partial Multi-Label Learning with Probabilistic Graphical Disambiguation. - Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez:
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks. - Luming Tang, Menglin Jia, Qianqian Wang, Cheng Perng Phoo, Bharath Hariharan:
Emergent Correspondence from Image Diffusion. - Yihe Deng, Yu Yang, Baharan Mirzasoleiman, Quanquan Gu:
Robust Learning with Progressive Data Expansion Against Spurious Correlation. - Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran:
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria. - Kruno Lehman, Alain Durmus, Umut Simsekli:
Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent. - Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang:
Uncovering Neural Scaling Laws in Molecular Representation Learning. - Cameron Smith, Yilun Du, Ayush Tewari, Vincent Sitzmann:
FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow. - Milad Sefidgaran, Abdellatif Zaidi, Piotr Krasnowski:
Minimum Description Length and Generalization Guarantees for Representation Learning. - Robin San Roman, Yossi Adi, Antoine Deleforge, Romain Serizel, Gabriel Synnaeve, Alexandre Défossez:
From Discrete Tokens to High-Fidelity Audio Using Multi-Band Diffusion. - Rajat Vadiraj Dwaraknath, Tolga Ergen, Mert Pilanci:
Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs. - Alberto Bietti, Vivien Cabannes, Diane Bouchacourt, Hervé Jégou, Léon Bottou:
Birth of a Transformer: A Memory Viewpoint. - Hoomaan Maskan, Konstantinos Zygalakis, Alp Yurtsever:
A Variational Perspective on High-Resolution ODEs. - Michal Yarom, Yonatan Bitton, Soravit Changpinyo, Roee Aharoni, Jonathan Herzig, Oran Lang, Eran Ofek, Idan Szpektor:
What You See is What You Read? Improving Text-Image Alignment Evaluation. - Anuran Makur, Marios Mertzanidis, Alexandros Psomas, Athina Terzoglou:
On the Robustness of Mechanism Design under Total Variation Distance. - Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai, Himabindu Lakkaraju, Haoyi Xiong:
M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models. - Tom M. George, Kimberly L. Stachenfeld, Caswell Barry, Claudia Clopath, Tomoki Fukai:
A generative model of the hippocampal formation trained with theta driven local learning rules. - James Queeney, Mouhacine Benosman:
Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning. - Paul Geuchen, Felix Voigtländer:
Optimal approximation using complex-valued neural networks. - Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong:
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery. - Leonard Papenmeier, Luigi Nardi, Matthias Poloczek:
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces. - Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli:
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. - Haonan Wang, Xiaomeng Li:
Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation. - Dachao Lin, Yuze Han, Haishan Ye, Zhihua Zhang:
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis. - Jiacheng Chen, Ruizhi Deng, Yasutaka Furukawa:
PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models. - Boris van Breugel, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar:
Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data. - Xiaosen Wang, Kangheng Tong, Kun He:
Rethinking the Backward Propagation for Adversarial Transferability. - Yiting Dong, Yang Li, Dongcheng Zhao, Guobin Shen, Yi Zeng:
Bullying10K: A Large-Scale Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition. - Zongyu Guo, Gergely Flamich, Jiajun He, Zhibo Chen, José Miguel Hernández-Lobato:
Compression with Bayesian Implicit Neural Representations. - Meghdad Kurmanji, Peter Triantafillou, Jamie Hayes, Eleni Triantafillou:
Towards Unbounded Machine Unlearning. - Dongyang Fan, Celestine Mendler-Dünner, Martin Jaggi:
Collaborative Learning via Prediction Consensus. - Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang:
Identification of Nonlinear Latent Hierarchical Models. - Honghao Wei, Xin Liu, Weina Wang, Lei Ying:
Sample Efficient Reinforcement Learning in Mixed Systems through Augmented Samples and Its Applications to Queueing Networks. - Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany:
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. - Taehyeon Kim, Eric Lin, Junu Lee, Christian Lau, Vaikkunth Mugunthan:
Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Approach for Object Detection. - Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian:
On the Generalization Properties of Diffusion Models. - Seokin Seo, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim:
Regularized Behavior Cloning for Blocking the Leakage of Past Action Information. - Yannai A. Gonczarowski, Gregory Kehne, Ariel D. Procaccia, Ben Schiffer, Shirley Zhang:
The Distortion of Binomial Voting Defies Expectation. - Xin Li, Sima Behpour, Thang Long Doan, Wenbin He, Liang Gou, Liu Ren:
UP-DP: Unsupervised Prompt Learning for Data Pre-Selection with Vision-Language Models. - Austin Watkins, Enayat Ullah, Thanh Nguyen-Tang, Raman Arora:
Optimistic Rates for Multi-Task Representation Learning. - Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim M. Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby:
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. - Kaiwen Wang, Kevin Zhou, Runzhe Wu, Nathan Kallus, Wen Sun:
The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning. - Francis Ward, Francesca Toni, Francesco Belardinelli, Tom Everitt:
Honesty Is the Best Policy: Defining and Mitigating AI Deception. - Oussama Boussif, Ghait Boukachab, Dan Assouline, Stefano Massaroli, Tianle Yuan, Loubna Benabbou, Yoshua Bengio:
Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context. - Yan Liu, Xiaokang Chen, Yan Gao, Zhe Su, Fengji Zhang, Daoguang Zan, Jian-Guang Lou, Pin-Yu Chen, Tsung-Yi Ho:
Uncovering and Quantifying Social Biases in Code Generation. - Yan Zhuang, Qi Liu, Guanhao Zhao, Zhenya Huang, Weizhe Huang, Zachary A. Pardos, Enhong Chen, Jinze Wu, Xin Li:
A Bounded Ability Estimation for Computerized Adaptive Testing. - Samuel Dooley, Gurnoor Singh Khurana, Chirag Mohapatra, Siddartha V. Naidu, Colin White:
ForecastPFN: Synthetically-Trained Zero-Shot Forecasting. - Fabian Zaiser, Andrzej S. Murawski, Chih-Hao Luke Ong:
Exact Bayesian Inference on Discrete Models via Probability Generating Functions: A Probabilistic Programming Approach. - Yinshuang Xu, Jiahui Lei, Kostas Daniilidis:
SE(3) Equivariant Convolution and Transformer in Ray Space. - Zhiqing Sun, Yikang Shen, Qinhong Zhou, Hongxin Zhang, Zhenfang Chen, David D. Cox, Yiming Yang, Chuang Gan:
Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision. - Weiliang Tang, Biqi Yang, Xianzhi Li, Yun-Hui Liu, Pheng-Ann Heng, Chi-Wing Fu:
Prototypical Variational Autoencoder for 3D Few-shot Object Detection. - David Yu-Tung Hui, Aaron C. Courville, Pierre-Luc Bacon:
Double Gumbel Q-Learning. - Jiangxing Wang, Deheng Ye, Zongqing Lu:
Mutual-Information Regularized Multi-Agent Policy Iteration. - Xue Yan, Jiaxian Guo, Xingzhou Lou, Jun Wang, Haifeng Zhang, Yali Du:
An Efficient End-to-End Training Approach for Zero-Shot Human-AI Coordination. - Brian Hu Zhang, Gabriele Farina, Ioannis Anagnostides, Federico Cacciamani, Stephen McAleer, Andreas A. Haupt, Andrea Celli, Nicola Gatti, Vincent Conitzer, Tuomas Sandholm:
Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games. - James Oldfield, Christos Tzelepis, Yannis Panagakis, Mihalis Nicolaou, Ioannis Patras:
Parts of Speech-Grounded Subspaces in Vision-Language Models. - Frederik Kunstner, Victor Sanches Portella, Mark Schmidt, Nicholas J. A. Harvey:
Searching for Optimal Per-Coordinate Step-sizes with Multidimensional Backtracking. - Yibo Yang, Stephan Eckstein, Marcel Nutz, Stephan Mandt:
Estimating the Rate-Distortion Function by Wasserstein Gradient Descent. - Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy:
Epistemic Neural Networks. - Peiyan Dong, Zhenglun Kong, Xin Meng, Pinrui Yu, Yifan Gong, Geng Yuan, Hao Tang, Yanzhi Wang:
HotBEV: Hardware-oriented Transformer-based Multi-View 3D Detector for BEV Perception. - Seungtae Nam, Daniel Rho, Jong Hwan Ko, Eunbyung Park:
Mip-Grid: Anti-aliased Grid Representations for Neural Radiance Fields. - Yatong Sun, Bin Wang, Zhu Sun, Xiaochun Yang, Yan Wang:
Theoretically Guaranteed Bidirectional Data Rectification for Robust Sequential Recommendation. - Silviu Pitis:
Consistent Aggregation of Objectives with Diverse Time Preferences Requires Non-Markovian Rewards. - Haotian Xue, Alexandre Araujo, Bin Hu, Yongxin Chen:
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability. - Muyang Li, Runze Wu, Haoyu Liu, Jun Yu, Xun Yang, Bo Han, Tongliang Liu:
InstanT: Semi-supervised Learning with Instance-dependent Thresholds. - Junlin Wu, Andrew Clark, Yiannis Kantaros, Yevgeniy Vorobeychik:
Neural Lyapunov Control for Discrete-Time Systems. - Aditya Chattopadhyay, Ryan Pilgrim, René Vidal:
Information Maximization Perspective of Orthogonal Matching Pursuit with Applications to Explainable AI. - Guan Wang, Yuhao Sun, Sijie Cheng, Sen Song:
Evolving Connectivity for Recurrent Spiking Neural Networks. - Sebastian Tay, Chuan Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low:
Bayesian Optimization with Cost-varying Variable Subsets. - Andong Wang, Chao Li, Mingyuan Bai, Zhong Jin, Guoxu Zhou, Qibin Zhao:
Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks. - Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Mehran Kazemi, Najoung Kim, He He:
Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. - Jacob Portes, Alexander Trott, Sam Havens, Daniel King, Abhinav Venigalla, Moin Nadeem, Nikhil Sardana, Daya Khudia, Jonathan Frankle:
MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining. - Xiao Zang, Miao Yin, Jinqi Xiao, Saman A. Zonouz, Bo Yuan:
GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search. - Hao Sun, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar:
Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples. - Zhaozhi Qian, Robert Davis, Mihaela van der Schaar:
Synthcity: a benchmark framework for diverse use cases of tabular synthetic data. - Philip Sun, David Simcha, Dave Dopson, Ruiqi Guo, Sanjiv Kumar:
SOAR: Improved Indexing for Approximate Nearest Neighbor Search. - Pha A. Nguyen, Kha Gia Quach, Kris Kitani, Khoa Luu:
Type-to-Track: Retrieve Any Object via Prompt-based Tracking. - Stratis Tsirtsis, Manuel Rodriguez:
Finding Counterfactually Optimal Action Sequences in Continuous State Spaces. - Yu Pan, Ye Yuan, Yichun Yin, Zenglin Xu, Lifeng Shang, Xin Jiang, Qun Liu:
Reusing Pretrained Models by Multi-linear Operators for Efficient Training. - AkshatKumar Nigam, Robert Pollice, Gary Tom, Kjell Jorner, John Willes, Luca A. Thiede, Anshul Kundaje, Alán Aspuru-Guzik:
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design. - Paul Yoo, Jiaxian Guo, Yutaka Matsuo, Shixiang Shane Gu:
DreamSparse: Escaping from Plato's Cave with 2D Diffusion Model Given Sparse Views. - Zhenyu Zhu, Francesco Locatello, Volkan Cevher:
Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling. - Kai Zhao, Qiyu Kang, Yang Song, Rui She, Sijie Wang, Wee Peng Tay:
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach. - Lesia Semenova, Harry Chen, Ronald Parr, Cynthia Rudin:
A Path to Simpler Models Starts With Noise. - Zirui Liu, Guanchu Wang, Shaochen (Henry) Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang (Ryan) Tang, Zhimeng Stephen Jiang, Kaixiong Zhou, Vipin Chaudhary, Shuai Xu, Xia Hu:
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model. - Yuyang Qiu, Uday V. Shanbhag, Farzad Yousefian:
Zeroth-Order Methods for Nondifferentiable, Nonconvex, and Hierarchical Federated Optimization. - Michael Noukhovitch, Samuel Lavoie, Florian Strub, Aaron C. Courville:
Language Model Alignment with Elastic Reset. - Junyi Li, Heng Huang:
Resolving the Tug-of-War: A Separation of Communication and Learning in Federated Learning. - Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David E. Evans:
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces. - Oscar Michel, Anand Bhattad, Eli VanderBilt, Ranjay Krishna, Aniruddha Kembhavi, Tanmay Gupta:
OBJECT 3DIT: Language-guided 3D-aware Image Editing. - Tianyu Liu, Qitan Lv, Jie Wang, Shuling Yang, Hanzhu Chen:
Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction. - Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, Gal Chechik:
Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment. - Qinghua Liu, Gellért Weisz, András György, Chi Jin, Csaba Szepesvári:
Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL. - Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong:
Two-Stage Learning to Defer with Multiple Experts. - Devvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S. Dhillon:
A Computationally Efficient Sparsified Online Newton Method. - Rainer Engelken:
SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks. - Senthil Purushwalkam, Nikhil Naik:
ConRad: Image Constrained Radiance Fields for 3D Generation from a Single Image. - Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Boning Tong, Jia Xu, Yanbo Feng, Qi Long, Li Shen:
Fair Canonical Correlation Analysis. - Zhiqing Sun, Yiming Yang:
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization. - George Stein, Jesse C. Cresswell, Rasa Hosseinzadeh, Yi Sui, Brendan Leigh Ross, Valentin Villecroze, Zhaoyan Liu, Anthony L. Caterini, J. Eric T. Taylor, Gabriel Loaiza-Ganem:
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models. - Zhiyong Wang, Jize Xie, Xutong Liu, Shuai Li, John C. S. Lui:
Online Clustering of Bandits with Misspecified User Models. - Gehua Ma, Runhao Jiang, Rui Yan, Huajin Tang:
Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes. - Soumya Basu, Abishek Sankararaman:
Double Auctions with Two-sided Bandit Feedback. - Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. - Seongsu Bae, Daeun Kyung, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei Ji, Eric I-Chao Chang, Tackeun Kim, Edward Choi:
EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images. - Tianyi Chen, Qidi Wang, Zhen Dong, Liwei Shen, Xin Peng:
Enhancing Robot Program Synthesis Through Environmental Context. - Quanyi Li, Zhenghao Mark Peng, Lan Feng, Zhizheng Liu, Chenda Duan, Wenjie Mo, Bolei Zhou:
ScenarioNet: Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling. - Haobo Zhang, Junyuan Hong, Yuyang Deng, Mehrdad Mahdavi, Jiayu Zhou:
Understanding Deep Gradient Leakage via Inversion Influence Functions. - Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji:
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization. - Saghar Adler, Vijay G. Subramanian:
Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space. - Xiao Luo, Haixin Wang, Zijie Huang, Huiyu Jiang, Abhijeet Gangan, Song Jiang, Yizhou Sun:
CARE: Modeling Interacting Dynamics Under Temporal Environmental Variation. - Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Soheil Feizi, Adrian Weller:
Diffused Redundancy in Pre-trained Representations. - Mohammadamin Tavakoli, Pierre Baldi, Ann Marie Carlton, Yin Ting T. Chiu, Alexander Shmakov, David Van Vranken:
AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning. - Jules Berman, Benjamin Peherstorfer:
Randomized Sparse Neural Galerkin Schemes for Solving Evolution Equations with Deep Networks. - Sara Pieri, Jose Renato Restom, Samuel Horváth, Hisham Cholakkal:
Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition. - Ajay Subramanian, Elena Sizikova, Najib J. Majaj, Denis G. Pelli:
Spatial-frequency channels, shape bias, and adversarial robustness. - Trung Dang, Jasper C. H. Lee, Maoyuan Raymond Song, Paul Valiant:
Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond 1+α Moments. - Hanlin Zhu, Amy Zhang:
Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability. - Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun:
SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions. - Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Driggs Campbell, Payel Das, Lav R. Varshney:
Efficient Equivariant Transfer Learning from Pretrained Models. - Sattar Vakili, Julia Olkhovskaya:
Kernelized Reinforcement Learning with Order Optimal Regret Bounds. - Haochen Li, Rui Zhang, Hantao Yao, Xinkai Song, Yifan Hao, Yongwei Zhao, Ling Li, Yunji Chen:
Learning Domain-Aware Detection Head with Prompt Tuning. - Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, Nima Anari:
Parallel Sampling of Diffusion Models. - Tao Wang, Sylvia L. Herbert, Sicun Gao:
Fractal Landscapes in Policy Optimization. - Sander Beckers:
Moral Responsibility for AI Systems. - Jeffrey Li, Jieyu Zhang, Ludwig Schmidt, Alexander J. Ratner:
Characterizing the Impacts of Semi-supervised Learning for Weak Supervision. - Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi:
Logarithmic Bayes Regret Bounds. - Keji He, Chenyang Si, Zhihe Lu, Yan Huang, Liang Wang, Xinchao Wang:
Frequency-Enhanced Data Augmentation for Vision-and-Language Navigation. - Sunipa Dev, Jaya Goyal, Dinesh Tewari, Shachi Dave, Vinodkumar Prabhakaran:
Building Socio-culturally Inclusive Stereotype Resources with Community Engagement. - Hao Liu, Wilson Yan, Pieter Abbeel:
Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment. - Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, Christopher De Sa:
QuIP: 2-Bit Quantization of Large Language Models With Guarantees. - Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low:
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits. - Yifan Xu, Mengdan Zhang, Chaoyou Fu, Peixian Chen, Xiaoshan Yang, Ke Li, Changsheng Xu:
Multi-modal Queried Object Detection in the Wild. - Anqi Mao, Mehryar Mohri, Yutao Zhong:
H-Consistency Bounds: Characterization and Extensions. - Peiyao Xiao, Hao Ban, Kaiyi Ji:
Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms. - Zhiyuan Yan, Yong Zhang, Xinhang Yuan, Siwei Lyu, Baoyuan Wu:
DeepfakeBench: A Comprehensive Benchmark of Deepfake Detection. - Yukun Huang, Jianan Wang, Ailing Zeng, He Cao, Xianbiao Qi, Yukai Shi, Zheng-Jun Zha, Lei Zhang:
DreamWaltz: Make a Scene with Complex 3D Animatable Avatars. - Chuanruo Ning, Ruihai Wu, Haoran Lu, Kaichun Mo, Hao Dong:
Where2Explore: Few-shot Affordance Learning for Unseen Novel Categories of Articulated Objects. - Gustaf Ahdritz, Nazim Bouatta, Sachin Kadyan, Lukas Jarosch, Daniel Berenberg, Ian Fisk, Andrew M. Watkins, Stephen Ra, Richard Bonneau, Mohammed AlQuraishi:
OpenProteinSet: Training data for structural biology at scale. - Palak Jain, Iden Kalemaj, Sofya Raskhodnikova, Satchit Sivakumar, Adam D. Smith:
Counting Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation. - Huy Nguyen, TrungTin Nguyen, Nhat Ho:
Demystifying Softmax Gating Function in Gaussian Mixture of Experts. - Hanlin Yang, Chao Yu, Peng Sun, Siji Chen:
Hybrid Policy Optimization from Imperfect Demonstrations. - Hao Sun, Boris van Breugel, Jonathan Crabbé, Nabeel Seedat, Mihaela van der Schaar:
What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization. - Jungtaek Kim, Mingxuan Li, Oliver Hinder, Paul W. Leu:
Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations. - Eeshaan Jain, Tushar Nandy, Gaurav Aggarwal, Ashish Tendulkar, Rishabh K. Iyer, Abir De:
Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks. - Wei Zheng, James Cheng Peng, Zeyuan Hou, Boyu Lyu, Mengfan Wang, Xuelong Mi, Shuoxuan Qiao, Yinan Wan, Guoqiang Yu:
NIS3D: A Completely Annotated Benchmark for Dense 3D Nuclei Image Segmentation. - Muxi Chen, Yu Li, Qiang Xu:
HiBug: On Human-Interpretable Model Debug. - Tin Sum Cheng, Aurélien Lucchi, Anastasis Kratsios, Ivan Dokmanic, David Belius:
A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression. - Alan Wang, Minh Nguyen, Mert R. Sabuncu:
Learning Invariant Representations with a Nonparametric Nadaraya-Watson Head. - Yu Gui, Rina Barber, Cong Ma:
Conformalized matrix completion. - Yuyang Deng, Ilja Kuzborskij, Mehrdad Mahdavi:
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation. - Emaad Khwaja, Yun Song, Aaron Agarunov, Bo Huang:
CELLE-2: Translating Proteins to Pictures and Back with a Bidirectional Text-to-Image Transformer. - Xiao Han, Yukang Cao, Kai Han, Xiatian Zhu, Jiankang Deng, Yi-Zhe Song, Tao Xiang, Kwan-Yee K. Wong:
HeadSculpt: Crafting 3D Head Avatars with Text. - Zhen Xiang, Zidi Xiong, Bo Li:
CBD: A Certified Backdoor Detector Based on Local Dominant Probability. - Hongxin Li, Jingran Su, Yuntao Chen, Qing Li, Zhaoxiang Zhang:
SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models. - Zhang-Wei Hong, Aviral Kumar, Sathwik Karnik, Abhishek Bhandwaldar, Akash Srivastava, Joni Pajarinen, Romain Laroche, Abhishek Gupta, Pulkit Agrawal:
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets. - Sangwoong Yoon, Frank C. Park, Gunsu S. Yun, Iljung Kim, Yung-Kyun Noh:
Variational Weighting for Kernel Density Ratios. - Odelia Melamed, Gilad Yehudai, Gal Vardi:
Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces. - Xingang Guo, Darioush Keivan, Geir E. Dullerud, Peter J. Seiler, Bin Hu:
Complexity of Derivative-Free Policy Optimization for Structured H∞ Control. - Anh Nguyen, Nikos Karampatziakis, Weizhu Chen:
Meet in the Middle: A New Pre-training Paradigm. - Tejas Jayashankar, Gary C. F. Lee, Alejandro Lancho, Amir Weiss, Yury Polyanskiy, Gregory W. Wornell:
Score-based Source Separation with Applications to Digital Communication Signals. - Junghyun Lee, Hanseul Cho, Se-Young Yun, Chulhee Yun:
Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint. - Ge Zheng, Bin Yang, Jiajin Tang, Hong-Yu Zhou, Sibei Yang:
DDCoT: Duty-Distinct Chain-of-Thought Prompting for Multimodal Reasoning in Language Models. - Tosca Lechner, Vinayak Pathak, Ruth Urner:
Adversarially Robust Learning with Uncertain Perturbation Sets. - Xiaoran Hao, Yash Jhaveri, Patrick Shafto:
Common Ground in Cooperative Communication. - Chao Li, Chen Gong, Qiang He, Xinwen Hou:
Keep Various Trajectories: Promoting Exploration of Ensemble Policies in Continuous Control. - Huikang Liu, Xiao Li, Anthony Man-Cho So:
ReSync: Riemannian Subgradient-based Robust Rotation Synchronization. - Zhijian Zhou, Jie Ni, Jia-He Yao, Wei Gao:
On the Exploration of Local Significant Differences For Two-Sample Test. - Xiaolong Wang, Runsen Xu, Zhuofan Cui, Zeyu Wan, Yu Zhang:
Fine-Grained Cross-View Geo-Localization Using a Correlation-Aware Homography Estimator. - Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi:
DataPerf: Benchmarks for Data-Centric AI Development. - Quanqi Hu, Dixian Zhu, Tianbao Yang:
Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization. - Hao Wang, Jiajun Fan, Zhichao Chen, Haoxuan Li, Weiming Liu, Tianqiao Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang:
Optimal Transport for Treatment Effect Estimation. - Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher:
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks. - Xiangyu Sun, Oliver Schulte:
Cause-Effect Inference in Location-Scale Noise Models: Maximum Likelihood vs. Independence Testing. - Wenxuan Zhang, Mahani Aljunied, Chang Gao, Yew Ken Chia, Lidong Bing:
M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models. - Anthony Fuller, Koreen Millard, James R. Green:
CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked Autoencoders. - Yingqiang Ge, Wenyue Hua, Kai Mei, Jianchao Ji, Juntao Tan, Shuyuan Xu, Zelong Li, Yongfeng Zhang:
OpenAGI: When LLM Meets Domain Experts. - Ruofan Wu, Jiawei Qiao, Mingzhe Wu, Wen Yu, Ming Zheng, Tengfei Liu, Tianyi Zhang, Weiqiang Wang:
Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions. - Shangtong Gui, Chenze Shao, Zhengrui Ma, Xishan Zhang, Yunji Chen, Yang Feng:
Non-autoregressive Machine Translation with Probabilistic Context-free Grammar. - Jing Zhang, Chi Zhang, Wenjia Wang, Bingyi Jing:
Constrained Policy Optimization with Explicit Behavior Density For Offline Reinforcement Learning. - Saeid Alavi Naeini, Raeid Saqur, Mozhgan Saeidi, John M. Giorgi, Babak Taati:
Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset. - Colin Bredenberg, Ezekiel Williams, Cristina Savin, Blake A. Richards, Guillaume Lajoie:
Formalizing locality for normative synaptic plasticity models. - Hongchao Zhang, Junlin Wu, Yevgeniy Vorobeychik, Andrew Clark:
Exact Verification of ReLU Neural Control Barrier Functions. - Sébastien Herbreteau, Emmanuel Moebel, Charles Kervrann:
Normalization-Equivariant Neural Networks with Application to Image Denoising. - Yao Liu, Pratik Chaudhari, Rasool Fakoor:
Budgeting Counterfactual for Offline RL. - Xidong Wu, Jianhui Sun, Zhengmian Hu, Junyi Li, Aidong Zhang, Heng Huang:
Federated Conditional Stochastic Optimization. - Muhammad Jehanzeb Mirza, Leonid Karlinsky, Wei Lin, Horst Possegger, Mateusz Kozinski, Rogério Feris, Horst Bischof:
LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections. - Chunlin Yu, Ye Shi, Jingya Wang:
Contextually Affinitive Neighborhood Refinery for Deep Clustering. - Tom Monnier, Jake Austin, Angjoo Kanazawa, Alexei A. Efros, Mathieu Aubry:
Differentiable Blocks World: Qualitative 3D Decomposition by Rendering Primitives. - Konwoo Kim, Gokul Swamy, Zuxin Liu, Ding Zhao, Sanjiban Choudhury, Zhiwei Steven Wu:
Learning Shared Safety Constraints from Multi-task Demonstrations. - Zhengxiang Shi, Aldo Lipani:
Don't Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner. - Haiteng Zhao, Shengchao Liu, Chang Ma, Hannan Xu, Jie Fu, Zhihong Deng, Lingpeng Kong, Qi Liu:
GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning. - Sungyub Kim, Kyungsu Kim, Eunho Yang:
GEX: A flexible method for approximating influence via Geometric Ensemble. - Dhawal Gupta, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier:
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. - Wei Wang, Lei Feng, Yuchen Jiang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama:
Binary Classification with Confidence Difference. - Vaishnavh Nagarajan, Aditya Krishna Menon, Srinadh Bhojanapalli, Hossein Mobahi, Sanjiv Kumar:
On student-teacher deviations in distillation: does it pay to disobey? - Victor Letzelter, Mathieu Fontaine, Mickaël Chen, Patrick Pérez, Slim Essid, Gaël Richard:
Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysis. - Aditya Shahane, Saripilli Swapna Manjiri, Ankesh Jain, Sandeep Kumar:
Graph of Circuits with GNN for Exploring the Optimal Design Space. - Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan:
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data. - Jaemin Cho, Abhay Zala, Mohit Bansal:
Visual Programming for Step-by-Step Text-to-Image Generation and Evaluation. - Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas:
Auditing Fairness by Betting. - Md Ashiqur Rahman, Raymond A. Yeh:
Truly Scale-Equivariant Deep Nets with Fourier Layers. - Jincheng Cao, Ruichen Jiang, Nazanin Abolfazli, Erfan Yazdandoost Hamedani, Aryan Mokhtari:
Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem. - Ziyu Chen, Wei Zhu:
On the Implicit Bias of Linear Equivariant Steerable Networks. - Moïse Blanchard, Junhui Zhang, Patrick Jaillet:
Memory-Constrained Algorithms for Convex Optimization. - Scott Alexander Cameron, Arnu Pretorius, Stephen J. Roberts:
Nonparametric Boundary Geometry in Physics Informed Deep Learning. - Joe Suk, Samory Kpotufe:
Tracking Most Significant Shifts in Nonparametric Contextual Bandits. - An Zhang, Leheng Sheng, Zhibo Cai, Xiang Wang, Tat-Seng Chua:
Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss. - Jon Donnelly, Srikar Katta, Cynthia Rudin, Edward P. Browne:
The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance. - Ziang Liu, Genggeng Zhou, Jeff He, Tobia Marcucci, Fei-Fei Li, Jiajun Wu, Yunzhu Li:
Model-Based Control with Sparse Neural Dynamics. - Shaokai Ye, Jessy Lauer, Mu Zhou, Alexander Mathis, Mackenzie W. Mathis:
AmadeusGPT: a natural language interface for interactive animal behavioral analysis. - Yuan Cheng, Jing Yang, Yingbin Liang:
Provably Efficient Algorithm for Nonstationary Low-Rank MDPs. - Paul Mineiro, Steven R. Howard:
Time-uniform confidence bands for the CDF under nonstationarity. - Yuchao Qin, Mihaela van der Schaar, Changhee Lee:
Risk-Averse Active Sensing for Timely Outcome Prediction under Cost Pressure. - Konstantin Makarychev, Sayak Chakrabarty:
Single-Pass Pivot Algorithm for Correlation Clustering. Keep it simple! - Yi-Chung Chen, Hsi-Wen Chen, Shun-Gui Wang, Ming-Syan Chen:
SPACE: Single-round Participant Amalgamation for Contribution Evaluation in Federated Learning. - Ziyuan Ye, Rihan Huang, Qilin Wu, Quanying Liu:
SAME: Uncovering GNN Black Box with Structure-aware Shapley-based Multipiece Explanations. - Michael Crawshaw, Yajie Bao, Mingrui Liu:
Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds. - Anwar Said, Roza G. Bayrak, Tyler Derr, Mudassir Shabbir, Daniel Moyer, Catie Chang, Xenofon D. Koutsoukos:
NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics. - Daniel Freund, Thodoris Lykouris, Wentao Weng:
Quantifying the Cost of Learning in Queueing Systems. - Ba-Hien Tran, Giulio Franzese, Pietro Michiardi, Maurizio Filippone:
One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models. - Qing Su, Anton Netchaev, Hai Li, Shihao Ji:
FLSL: Feature-level Self-supervised Learning. - Dipam Goswami, Yuyang Liu, Bartlomiej Twardowski, Joost van de Weijer:
FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning. - Aoyang Qin, Feng Gao, Qing Li, Song-Chun Zhu, Sirui Xie:
Learning non-Markovian Decision-Making from State-only Sequences. - Zeyang Zhang, Xin Wang, Ziwei Zhang, Zhou Qin, Weigao Wen, Hui Xue, Haoyang Li, Wenwu Zhu:
Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts. - Garrett Bingham, Risto Miikkulainen:
Efficient Activation Function Optimization through Surrogate Modeling. - Sai Srivatsa Ravindranath, Yanchen Jiang, David C. Parkes:
Data Market Design through Deep Learning. - Xinhong Ma, Yiming Wang, Hao Liu, Tianyu Guo, Yunhe Wang:
When Visual Prompt Tuning Meets Source-Free Domain Adaptive Semantic Segmentation. - Qiuyu Wang, Zifan Shi, Kecheng Zheng, Yinghao Xu, Sida Peng, Yujun Shen:
Benchmarking and Analyzing 3D-aware Image Synthesis with a Modularized Codebase. - Zhecheng Yuan, Sizhe Yang, Pu Hua, Can Chang, Kaizhe Hu, Huazhe Xu:
RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization. - Ahmed Khaled, Konstantin Mishchenko, Chi Jin:
DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method. - Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause:
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. - Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yian Ma:
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation. - Yunqi Shi, Ke Xue, Song Lei, Chao Qian:
Macro Placement by Wire-Mask-Guided Black-Box Optimization. - Yuchen Yan, Baoyu Jing, Lihui Liu, Ruijie Wang, Jinning Li, Tarek F. Abdelzaher, Hanghang Tong:
Reconciling Competing Sampling Strategies of Network Embedding. - Hamed Nilforoshan, Michael Moor, Yusuf Roohani, Yining Chen, Anja Surina, Michihiro Yasunaga, Sara Oblak, Jure Leskovec:
Zero-shot causal learning. - Ceyuan Yang, Qihang Zhang, Yinghao Xu, Jiapeng Zhu, Yujun Shen, Bo Dai:
Learning Modulated Transformation in GANs. - Xichen Ye, Xiaoqiang Li, Songmin Dai, Tong Liu, Yan Sun, Weiqin Tong:
Active Negative Loss Functions for Learning with Noisy Labels. - Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel:
Compositional Generalization from First Principles. - Zheng Chen, Yan-Pei Cao, Yuan-Chen Guo, Chen Wang, Ying Shan, Song-Hai Zhang:
PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas. - Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy:
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. - Xuyang Chen, Lin Zhao:
Finite-Time Analysis of Single-Timescale Actor-Critic. - Hanting Chen, Yunhe Wang, Jianyuan Guo, Dacheng Tao:
VanillaNet: the Power of Minimalism in Deep Learning. - Dominik Straub, Matthias Schultheis, Heinz Koeppl, Constantin A. Rothkopf:
Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs. - Prateek Yadav, Derek Tam, Leshem Choshen, Colin A. Raffel, Mohit Bansal:
TIES-Merging: Resolving Interference When Merging Models. - Haotian Xue, Antonio Torralba, Josh Tenenbaum, Dan Yamins, Yunzhu Li, Hsiao-Yu Tung:
3D-IntPhys: Towards More Generalized 3D-grounded Visual Intuitive Physics under Challenging Scenes. - Weijian Luo, Boya Zhang, Zhihua Zhang:
Entropy-based Training Methods for Scalable Neural Implicit Samplers. - Hyungjin Chung, Jeongsol Kim, Jong Chul Ye:
Direct Diffusion Bridge using Data Consistency for Inverse Problems. - Yuetian Weng, Mingfei Han, Haoyu He, Mingjie Li, Lina Yao, Xiaojun Chang, Bohan Zhuang:
Mask Propagation for Efficient Video Semantic Segmentation. - Shai Ben-David, Alex Bie, Clément L. Canonne, Gautam Kamath, Vikrant Singhal:
Private Distribution Learning with Public Data: The View from Sample Compression. - Xidong Feng, Yicheng Luo, Ziyan Wang, Hongrui Tang, Mengyue Yang, Kun Shao, David Mguni, Yali Du, Jun Wang:
ChessGPT: Bridging Policy Learning and Language Modeling. - Joon-Hyeok Yim, Anna A. Gilbert:
Fitting trees to 𝓁1-hyperbolic distances. - Daolang Huang, Ayush Bharti, Amauri H. Souza, Luigi Acerbi, Samuel Kaski:
Learning Robust Statistics for Simulation-based Inference under Model Misspecification. - Jonathan Pilault, Mahan Fathi, Orhan Firat, Chris Pal, Pierre-Luc Bacon, Ross Goroshin:
Block-State Transformers. - David S. Watson, Joshua O'Hara, Niek Tax, Richard Mudd, Ido Guy:
Explaining Predictive Uncertainty with Information Theoretic Shapley Values. - Thoranna Bender, Simon Møe Sørensen, Alireza Kashani, Kristjan Eldjarn Hjorleifsson, Grethe Hyldig, Søren Hauberg, Serge J. Belongie, Frederik Warburg:
Learning to Taste: A Multimodal Wine Dataset. - Charles Guille-Escuret, Pau Rodríguez, David Vázquez, Ioannis Mitliagkas, João Monteiro:
CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning. - Neeratyoy Mallik, Edward Bergman, Carl Hvarfner, Danny Stoll, Maciej Janowski, Marius Lindauer, Luigi Nardi, Frank Hutter:
PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning. - Muhammad Salman Ali, Yeongwoong Kim, Maryam Qamar, Sung-Chang Lim, Donghyun Kim, Chaoning Zhang, Sung-Ho Bae, Hui Yong Kim:
Towards Efficient Image Compression Without Autoregressive Models. - Xiuyuan Hu, Guoqing Liu, Yang Zhao, Hao Zhang:
De novo Drug Design using Reinforcement Learning with Multiple GPT Agents. - Luke Travis, Kolyan Ray:
Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior. - Zhibin Duan, Zhiyi Lv, Chaojie Wang, Bo Chen, Bo An, Mingyuan Zhou:
Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory. - Joseph T. Costello, Hisham Temmar, Luis Cubillos, Matthew Mender, Dylan Wallace, Matt S. Willsey, Parag G. Patil, Cynthia A. Chestek:
Balancing memorization and generalization in RNNs for high performance brain-machine Interfaces. - Scott Pesme, Nicolas Flammarion:
Saddle-to-Saddle Dynamics in Diagonal Linear Networks. - Guanghui Yu, Wei Tang, Saumik Narayanan, Chien-Ju Ho:
Encoding Human Behavior in Information Design through Deep Learning. - Chen Cheng, Gary Cheng, John C. Duchi:
Collaboratively Learning Linear Models with Structured Missing Data. - Shashank Hegde, Sumeet Batra, K. R. Zentner, Gaurav S. Sukhatme:
Generating Behaviorally Diverse Policies with Latent Diffusion Models. - Rachael Hwee Ling Sim, Yehong Zhang, Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet:
Incentives in Private Collaborative Machine Learning. - Xiang Wang, Hangjie Yuan, Shiwei Zhang, Dayou Chen, Jiuniu Wang, Yingya Zhang, Yujun Shen, Deli Zhao, Jingren Zhou:
VideoComposer: Compositional Video Synthesis with Motion Controllability. - Peng Cheng, Xianyuan Zhan, Zhi-Hao Wu, Wenjia Zhang, Youfang Lin, Shoucheng Song, Han Wang, Li Jiang:
Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL. - Roey Magen, Ohad Shamir:
Initialization-Dependent Sample Complexity of Linear Predictors and Neural Networks. - Florian E. Dorner, Nikola Konstantinov, Georgi Pashaliev, Martin T. Vechev:
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization. - Paul-Edouard Sarlin, Eduard Trulls, Marc Pollefeys, Jan Hosang, Simon Lynen:
SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding. - Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John D. Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Yang, Brandyn White, Aleksandra Faust, Rowan McAllister, Dragomir Anguelov, Benjamin Sapp:
Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research. - Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu:
Equal Opportunity of Coverage in Fair Regression. - Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok:
Nonparametric Teaching for Multiple Learners. - Angelica Chen, David Dohan, David R. So:
EvoPrompting: Language Models for Code-Level Neural Architecture Search. - Zechuan Zhang, Li Sun, Zongxin Yang, Ling Chen, Yi Yang:
Global-correlated 3D-decoupling Transformer for Clothed Avatar Reconstruction. - Pum Jun Kim, Yoojin Jang, Jisu Kim, Jaejun Yoo:
TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models. - Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding:
A Unified Detection Framework for Inference-Stage Backdoor Defenses. - Qinyi Chen, Negin Golrezaei, Djallel Bouneffouf:
Non-Stationary Bandits with Auto-Regressive Temporal Dependency. - Martin Ryner, Jan Kronqvist, Johan Karlsson:
Globally solving the Gromov-Wasserstein problem for point clouds in low dimensional Euclidean spaces. - Félix Chalumeau, Shikha Surana, Clément Bonnet, Nathan Grinsztajn, Arnu Pretorius, Alexandre Laterre, Tom Barrett:
Combinatorial Optimization with Policy Adaptation using Latent Space Search. - Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey:
SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking. - Dongwei Pan, Long Zhuo, Jingtan Piao, Huiwen Luo, Wei Cheng, Yuxin Wang, Siming Fan, Shengqi Liu, Lei Yang, Bo Dai, Ziwei Liu, Chen Change Loy, Chen Qian, Wayne Wu, Dahua Lin, Kwan-Yee Lin:
RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars. - Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang:
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. - Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty:
Adversarial Resilience in Sequential Prediction via Abstention. - Depen Morwani, Jatin Batra, Prateek Jain, Praneeth Netrapalli:
Simplicity Bias in 1-Hidden Layer Neural Networks. - Elysia Q. Smyers, Sydney M. Katz, Anthony Corso, Mykel J. Kochenderfer:
AVOIDDS: Aircraft Vision-based Intruder Detection Dataset and Simulator. - Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric P. Xing, Kun Zhang:
Temporally Disentangled Representation Learning under Unknown Nonstationarity. - Ruichen Jiang, Aryan Mokhtari:
Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization. - Tao Lei, Junwen Bai, Siddhartha Brahma, Joshua Ainslie, Kenton Lee, Yanqi Zhou, Nan Du, Vincent Y. Zhao, Yuexin Wu, Bo Li, Yu Zhang, Ming-Wei Chang:
Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference. - Futoshi Futami, Masahiro Fujisawa:
Time-Independent Information-Theoretic Generalization Bounds for SGLD. - Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen:
Topology-Aware Uncertainty for Image Segmentation. - Atli Kosson, Martin Jaggi:
Multiplication-Free Transformer Training via Piecewise Affine Operations. - Junren Chen, Jonathan Scarlett, Michael Ng, Zhaoqiang Liu:
A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing. - Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi:
Tempo Adaptation in Non-stationary Reinforcement Learning. - Eric Hedlin, Gopal Sharma, Shweta Mahajan, Hossam Isack, Abhishek Kar, Andrea Tagliasacchi, Kwang Moo Yi:
Unsupervised Semantic Correspondence Using Stable Diffusion. - Zhenxing Ge, Zheng Xu, Tianyu Ding, Wenbin Li, Yang Gao:
Efficient Subgame Refinement for Extensive-form Games. - Yuanze Wang, Yichao Yan, Dianxi Shi, Wenhan Zhu, Jianqiang Xia, Jeff Tan, Songchang Jin, Ke Gao, Xiaobo Li, Xiaokang Yang:
NeRF-IBVS: Visual Servo Based on NeRF for Visual Localization and Navigation. - Kaiqi Jiang, Dhruv Malik, Yuanzhi Li:
How Does Adaptive Optimization Impact Local Neural Network Geometry? - Benno Krojer, Elinor Poole-Dayan, Vikram Voleti, Chris Pal, Siva Reddy:
Are Diffusion Models Vision-And-Language Reasoners? - Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu:
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation. - Abdullah Alomar, Munther A. Dahleh, Sean Mann, Devavrat Shah:
SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise. - Ruiying Lu, YuJie Wu, Long Tian, Dongsheng Wang, Bo Chen, Xiyang Liu, Ruimin Hu:
Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection. - Yinan Liang, Ziwei Wang, Xiuwei Xu, Yansong Tang, Jie Zhou, Jiwen Lu:
MCUFormer: Deploying Vision Tranformers on Microcontrollers with Limited Memory. - Zhijie Deng, Peng Cui, Jun Zhu:
Towards Accelerated Model Training via Bayesian Data Selection. - Wanxing Chang, Ye Shi, Jingya Wang:
CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy Labels. - Zhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen, Pengcheng He, Weizhu Chen, Zhangyang (Atlas) Wang, Mingyuan Zhou:
In-Context Learning Unlocked for Diffusion Models. - Jindong Jiang, Fei Deng, Gautam Singh, Sungjin Ahn:
Object-Centric Slot Diffusion. - Dieterich Lawson, Michael Li, Scott W. Linderman:
NAS-X: Neural Adaptive Smoothing via Twisting. - Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, Shunyu Yao:
Reflexion: language agents with verbal reinforcement learning. - Kazuto Fukuchi, Jun Sakuma:
Demographic Parity Constrained Minimax Optimal Regression under Linear Model. - Vicente Vivanco Cepeda, Gaurav Kumar Nayak, Mubarak Shah:
GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization. - Haonan Yan, Wenjing Zhang, Qian Chen, Xiaoguang Li, Wenhai Sun, Hui Li, Xiaodong Lin:
RECESS Vaccine for Federated Learning: Proactive Defense Against Model Poisoning Attacks. - Jiyoung Park, Ian Pelakh, Stephan Wojtowytsch:
Minimum norm interpolation by perceptra: Explicit regularization and implicit bias. - Zihan Chen, Howard H. Yang, Tony Q. S. Quek, Kai Fong Ernest Chong:
Spectral Co-Distillation for Personalized Federated Learning. - Jingjing Li, Wei Ji, Size Wang, Wenbo Li, Li Cheng:
DVSOD: RGB-D Video Salient Object Detection. - Sanghyun Son, Laura Yu Zheng, Ryan Sullivan, Yi-Ling Qiao, Ming C. Lin:
Gradient Informed Proximal Policy Optimization. - Di Wang, Jing Zhang, Bo Du, Minqiang Xu, Lin Liu, Dacheng Tao, Liangpei Zhang:
SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model. - Hao Liu, Pieter Abbeel:
Blockwise Parallel Transformers for Large Context Models. - Fu Luo, Xi Lin, Fei Liu, Qingfu Zhang, Zhenkun Wang:
Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization. - Babak Esmaeili, Robin Walters, Heiko Zimmermann, Jan-Willem van de Meent:
Topological Obstructions and How to Avoid Them. - Spencer Frei, Gal Vardi, Peter L. Bartlett, Nati Srebro:
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks. - Cong Wang, Jinshan Pan, Wei Wang, Jiangxin Dong, Mengzhu Wang, Yakun Ju, Junyang Chen:
PromptRestorer: A Prompting Image Restoration Method with Degradation Perception. - Chenze Shao, Zhengrui Ma, Min Zhang, Yang Feng:
Beyond MLE: Convex Learning for Text Generation. - Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi:
Bandit Task Assignment with Unknown Processing Time. - Wanrong Zhu, Jack Hessel, Anas Awadalla, Samir Yitzhak Gadre, Jesse Dodge, Alex Fang, Youngjae Yu, Ludwig Schmidt, William Yang Wang, Yejin Choi:
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text. - Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan:
Towards Self-Interpretable Graph-Level Anomaly Detection. - Jingyuan Li, Leo Scholl, Trung Le, Pavithra Rajeswaran, Amy Orsborn, Eli Shlizerman:
AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity. - Peiyan Dong, Lei Lu, Chao Wu, Cheng Lyu, Geng Yuan, Hao Tang, Yanzhi Wang:
PackQViT: Faster Sub-8-bit Vision Transformers via Full and Packed Quantization on the Mobile. - Jiarui Feng, Lecheng Kong, Hao Liu, Dacheng Tao, Fuhai Li, Muhan Zhang, Yixin Chen:
Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman. - Qitong Gao, Ge Gao, Juncheng Dong, Vahid Tarokh, Min Chi, Miroslav Pajic:
Off-Policy Evaluation for Human Feedback. - Yash Bhalgat, Iro Laina, João F. Henriques, Andrea Vedaldi, Andrew Zisserman:
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion. - Yejiang Wang, Yuhai Zhao, Daniel Zhengkui Wang, Ling Li:
GALOPA: Graph Transport Learning with Optimal Plan Alignment. - Naoki Nishikawa, Yuichi Ike, Kenji Yamanishi:
Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds. - Shizhe Ding, Boyang Xia, Dongbo Bu:
Accurate Interpolation for Scattered Data through Hierarchical Residual Refinement. - Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, Pieter Abbeel:
Learning Universal Policies via Text-Guided Video Generation. - Jacobus G. M. van der Linden, Mathijs de Weerdt, Emir Demirovic:
Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming. - Tan Zhu, Fei Dou, Xinyu Wang, Jin Lu, Jinbo Bi:
Polyhedron Attention Module: Learning Adaptive-order Interactions. - Leyla Biabani, Annika Hennes, Morteza Monemizadeh, Melanie Schmidt:
Faster Query Times for Fully Dynamic k-Center Clustering with Outliers. - Jing-Cheng Pang, Xinyu Yang, Si-Hang Yang, Xiong-Hui Chen, Yang Yu:
Natural Language Instruction-following with Task-related Language Development and Translation. - Haoxing Tian, Alex Olshevsky, Yannis Paschalidis:
Convergence of Actor-Critic with Multi-Layer Neural Networks. - Cyrus Cousins, Elita A. Lobo, Marek Petrik, Yair Zick:
Percentile Criterion Optimization in Offline Reinforcement Learning. - Jingye Chen, Yupan Huang, Tengchao Lv, Lei Cui, Qifeng Chen, Furu Wei:
TextDiffuser: Diffusion Models as Text Painters. - Ziyu Wang, Mike Zheng Shou, Mengmi Zhang:
Object-centric Learning with Cyclic Walks between Parts and Whole. - Aldo Pacchiano, Jonathan Lee, Emma Brunskill:
Experiment Planning with Function Approximation. - Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin D. Haeffele, Yi Ma:
White-Box Transformers via Sparse Rate Reduction. - Jianghui Wang, Yang Chen, Xingyu Xie, Cong Fang, Zhouchen Lin:
Task-Robust Pre-Training for Worst-Case Downstream Adaptation. - Rie Johnson, Tong Zhang:
Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training. - Samantha Chen, Yusu Wang:
Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions. - Mengping Yang, Ceyuan Yang, Yichi Zhang, Qingyan Bai, Yujun Shen, Bo Dai:
Revisiting the Evaluation of Image Synthesis with GANs. - Shi Chen, Ming Jiang, Qi Zhao:
What Do Deep Saliency Models Learn about Visual Attention? - Valentino Delle Rose, Alexander Kozachinskiy, Cristobal Rojas, Mircea Petrache, Pablo Barceló:
Three Iterations of (d - 1)-WL Test Distinguish Non Isometric Clouds of d-dimensional Points. - Sepidehsadat (Sepid) Hossieni, Mohammad Amin Shabani, Saghar Irandoust, Yasutaka Furukawa:
Puzzlefusion: Unleashing the Power of Diffusion Models for Spatial Puzzle Solving. - Thao Nguyen, Yuheng Li, Utkarsh Ojha, Yong Jae Lee:
Visual Instruction Inversion: Image Editing via Image Prompting. - Jifan Zhang, Shuai Shao, Saurabh Verma, Robert D. Nowak:
Algorithm Selection for Deep Active Learning with Imbalanced Datasets. - Xinwen Zhang, Yihan Zhang, Tianbao Yang, Richard Souvenir, Hongchang Gao:
Federated Compositional Deep AUC Maximization. - Kaifu Wang, Efthymia Tsamoura, Dan Roth:
On Learning Latent Models with Multi-Instance Weak Supervision. - Leonard Tang, Dan Ley:
Degraded Polygons Raise Fundamental Questions of Neural Network Perception. - Blake Bordelon, Cengiz Pehlevan:
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks. - Kush Bhatia, Avanika Narayan, Christopher De Sa, Christopher Ré:
TART: A plug-and-play Transformer module for task-agnostic reasoning. - Carsten T. Lüth, Till J. Bungert, Lukas Klein, Paul F. Jaeger:
Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment. - Fabian Paischer, Thomas Adler, Markus Hofmarcher, Sepp Hochreiter:
Semantic HELM: A Human-Readable Memory for Reinforcement Learning. - Farnood Salehi, Tunç Ozan Aydin, André Gaillard, Guglielmo Camporese, Yuxuan Wang:
Empowering Convolutional Neural Nets with MetaSin Activation. - Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar:
When Does Confidence-Based Cascade Deferral Suffice? - Yiqun Duan, Charles Chau, Zhen Wang, Yu-Kai Wang, Chin-Teng Lin:
DeWave: Discrete Encoding of EEG Waves for EEG to Text Translation. - Bang An, Xun Zhou, Yongjian Zhong, Tianbao Yang:
SpatialRank: Urban Event Ranking with NDCG Optimization on Spatiotemporal Data. - Mohammad Jalali, Cheuk Ting Li, Farzan Farnia:
An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions. - Yaroslav Kivva, Saber Salehkaleybar, Negar Kiyavash:
A Cross-Moment Approach for Causal Effect Estimation. - Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew K. Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo Jimenez Rezende, Daniel Zoran:
Combining Behaviors with the Successor Features Keyboard. - Chenyu You, Weicheng Dai, Yifei Min, Fenglin Liu, David A. Clifton, S. Kevin Zhou, Lawrence H. Staib, James S. Duncan:
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective. - Jiaxu Tian, Dapeng Zhi, Si Liu, Peixin Wang, Cheng Chen, Min Zhang:
Boosting Verification of Deep Reinforcement Learning via Piece-Wise Linear Decision Neural Networks. - Andrey Okhotin, Dmitry Molchanov, Vladimir Arkhipkin, Grigory Bartosh, Viktor Ohanesian, Aibek Alanov, Dmitry P. Vetrov:
Star-Shaped Denoising Diffusion Probabilistic Models. - Alessio Mazzetto, Eli Upfal:
An Adaptive Algorithm for Learning with Unknown Distribution Drift. - Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer:
QLoRA: Efficient Finetuning of Quantized LLMs. - Ping Guo, Xiangpeng Wei, Yue Hu, Baosong Yang, Dayiheng Liu, Fei Huang, Jun Xie:
EMMA-X: An EM-like Multilingual Pre-training Algorithm for Cross-lingual Representation Learning. - Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan:
Tester-Learners for Halfspaces: Universal Algorithms. - Zhiwei Hao, Jianyuan Guo, Kai Han, Han Hu, Chang Xu, Yunhe Wang:
Revisit the Power of Vanilla Knowledge Distillation: from Small Scale to Large Scale. - Julian Tanke, Oh-Hun Kwon, Felix B. Mueller, Andreas Doering, Jürgen Gall:
Humans in Kitchens: A Dataset for Multi-Person Human Motion Forecasting with Scene Context. - Ningyi Liao, Siqiang Luo, Xiang Li, Jieming Shi:
LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings. - Aaron Zweig, Loucas Pillaud-Vivien, Joan Bruna:
On Single-Index Models beyond Gaussian Data. - Xiaoxiao Sun, Nidham Gazagnadou, Vivek Sharma, Lingjuan Lyu, Hongdong Li, Liang Zheng:
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception? - Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang:
Graph Denoising Diffusion for Inverse Protein Folding. - Chaofan Ma, Yuhuan Yang, Chen Ju, Fei Zhang, Ya Zhang, Yanfeng Wang:
Open-Vocabulary Semantic Segmentation via Attribute Decomposition-Aggregation. - Mitchell Wortsman, Tim Dettmers, Luke Zettlemoyer, Ari Morcos, Ali Farhadi, Ludwig Schmidt:
Stable and low-precision training for large-scale vision-language models. - Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Mahesh Sathiamoorthy:
Recommender Systems with Generative Retrieval. - Jinghuan Shang, Michael S. Ryoo:
Active Vision Reinforcement Learning under Limited Visual Observability. - Eduardo Sany Laber, Lucas Murtinho:
Optimization of Inter-group criteria for clustering with minimum size constraints. - Sihan Xu, Ziqiao Ma, Yidong Huang, Honglak Lee, Joyce Chai:
CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation. - Kiarash Banihashem, MohammadTaghi Hajiaghayi, Suho Shin, Aleksandrs Slivkins:
Bandit Social Learning under Myopic Behavior. - Rainer Engelken:
Gradient Flossing: Improving Gradient Descent through Dynamic Control of Jacobians. - Carlos Mougan, Richard Plant, Clare Teng, Marya Bazzi, Alvaro Cabrejas Egea, Ryan Sze-Yin Chan, David Salvador Jasin, Martin Stoffel, Kirstie J. Whitaker, Jules Manser:
How to Data in Datathons. - Théo Gnassounou, Rémi Flamary, Alexandre Gramfort:
Convolution Monge Mapping Normalization for learning on sleep data. - Nicolas Zucchet, Robert Meier, Simon Schug, Asier Mujika, João Sacramento:
Online learning of long-range dependencies. - Yueming Lyu:
Fast Rank-1 Lattice Targeted Sampling for Black-box Optimization. - Nikos Kolotouros, Thiemo Alldieck, Andrei Zanfir, Eduard Gabriel Bazavan, Mihai Fieraru, Cristian Sminchisescu:
DreamHuman: Animatable 3D Avatars from Text. - Daesung Kim, Hye Won Chung:
Rank-1 Matrix Completion with Gradient Descent and Small Random Initialization. - Mengzi Amy Guo, Donghao Ying, Javad Lavaei, Zuo-Jun Max Shen:
No-Regret Learning in Dynamic Competition with Reference Effects Under Logit Demand. - Bowen Li, Jiashun Wang, Yaoyu Hu, Chen Wang, Sebastian A. Scherer:
VoxDet: Voxel Learning for Novel Instance Detection. - Guangyuan Jiang, Manjie Xu, Song-Chun Zhu, Wenjuan Han, Chi Zhang, Yixin Zhu:
Evaluating and Inducing Personality in Pre-trained Language Models. - Christopher T. H. Teo, Milad Abdollahzadeh, Ngai-Man Cheung:
On Measuring Fairness in Generative Models. - Bochuan Cao, Changjiang Li, Ting Wang, Jinyuan Jia, Bo Li, Jinghui Chen:
IMPRESS: Evaluating the Resilience of Imperceptible Perturbations Against Unauthorized Data Usage in Diffusion-Based Generative AI. - Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman:
Robust Contrastive Language-Image Pretraining against Data Poisoning and Backdoor Attacks. - Darshan Chakrabarti, Jelena Diakonikolas, Christian Kroer:
Block-Coordinate Methods and Restarting for Solving Extensive-Form Games. - Jia Guo, Shuai Lu, Lize Jia, Weihang Zhang, Huiqi Li:
ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction. - Klim Kireev, Maksym Andriushchenko, Carmela Troncoso, Nicolas Flammarion:
Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings. - Chengsen Wang, Zirui Zhuang, Qi Qi, Jingyu Wang, Xingyu Wang, Haifeng Sun, Jianxin Liao:
Drift doesn't Matter: Dynamic Decomposition with Diffusion Reconstruction for Unstable Multivariate Time Series Anomaly Detection. - Zeyuan Ma, Hongshu Guo, Jiacheng Chen, Zhenrui Li, Guojun Peng, Yue-Jiao Gong, Yining Ma, Zhiguang Cao:
MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning. - Huafeng Kuang, Hong Liu, Yongjian Wu, Shin'ichi Satoh, Rongrong Ji:
Improving Adversarial Robustness via Information Bottleneck Distillation. - Xinyu Zhou, Pinxue Guo, Lingyi Hong, Jinglun Li, Wei Zhang, Weifeng Ge, Wenqiang Zhang:
Reading Relevant Feature from Global Representation Memory for Visual Object Tracking. - Eshaan Nichani, Alex Damian, Jason D. Lee:
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks. - Tiansheng Huang, Sihao Hu, Ka Ho Chow, Fatih Ilhan, Selim F. Tekin, Ling Liu:
Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training. - Yue Kang, Cho-Jui Hsieh, Thomas Chun Man Lee:
Robust Lipschitz Bandits to Adversarial Corruptions. - Langzhang Liang, Xiangjing Hu, Zenglin Xu, Zixing Song, Irwin King:
Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily. - Ruth Dannenfelser, Jeffrey Zhong, Ran Zhang, Vicky Yao:
Into the Single Cell Multiverse: an End-to-End Dataset for Procedural Knowledge Extraction in Biomedical Texts. - Hongyi Yuan, Zheng Yuan, Chuanqi Tan, Wei Wang, Songfang Huang, Fei Huang:
RRHF: Rank Responses to Align Language Models with Human Feedback. - Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
Sparsity-Preserving Differentially Private Training of Large Embedding Models. - Marcus Triplett, Marta Gajowa, Hillel Adesnik, Liam Paninski:
Bayesian target optimisation for high-precision holographic optogenetics. - Roy Uziel, Or Dinari, Oren Freifeld:
From ViT Features to Training-free Video Object Segmentation via Streaming-data Mixture Models. - David Mayo, Jesse Cummings, Xinyu Lin, Dan Gutfreund, Boris Katz, Andrei Barbu:
How hard are computer vision datasets? Calibrating dataset difficulty to viewing time. - Utkarsh Ojha, Yuheng Li, Anirudh Sundara Rajan, Yingyu Liang, Yong Jae Lee:
What Knowledge Gets Distilled in Knowledge Distillation? - Patric Bonnier, Harald Oberhauser, Zoltán Szabó:
Kernelized Cumulants: Beyond Kernel Mean Embeddings. - Aleksandar Stanic, Anand Gopalakrishnan, Kazuki Irie, Jürgen Schmidhuber:
Contrastive Training of Complex-Valued Autoencoders for Object Discovery. - Zacharia Issa, Blanka Horvath, Maud Lemercier, Cristopher Salvi:
Non-adversarial training of Neural SDEs with signature kernel scores. - Shihao Zhao, Dongdong Chen, Yen-Chun Chen, Jianmin Bao, Shaozhe Hao, Lu Yuan, Kwan-Yee K. Wong:
Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models. - Yan-Shuo Liang, Wu-Jun Li:
Loss Decoupling for Task-Agnostic Continual Learning. - Insu Jeon, Minui Hong, Junhyeog Yun, Gunhee Kim:
Federated Learning via Meta-Variational Dropout. - Xiran Fan, Chun-Hao Yang, Baba C. Vemuri:
Horospherical Decision Boundaries for Large Margin Classification in Hyperbolic Space. - Yuzhang Shang, Zhihang Yuan, Yan Yan:
MIM4DD: Mutual Information Maximization for Dataset Distillation. - Woojin Cho, Kookjin Lee, Donsub Rim, Noseong Park:
Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks. - Xidong Wu, Jianhui Sun, Zhengmian Hu, Aidong Zhang, Heng Huang:
Solving a Class of Non-Convex Minimax Optimization in Federated Learning. - Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Haitham Bou-Ammar:
End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes. - Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu:
Contextual Bandits and Imitation Learning with Preference-Based Active Queries. - George Ma, Yifei Wang, Yisen Wang:
Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding. - Jae Sung Park, Jack Hessel, Khyathi Raghavi Chandu, Paul Pu Liang, Ximing Lu, Peter West, Youngjae Yu, Qiuyuan Huang, Jianfeng Gao, Ali Farhadi, Yejin Choi:
Localized Symbolic Knowledge Distillation for Visual Commonsense Models. - Mengcheng Lan, Xinjiang Wang, Yiping Ke, Jiaxing Xu, Litong Feng, Wayne Zhang:
SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation. - Junjiao Tian, Yen-Cheng Liu, James Seale Smith, Zsolt Kira:
Fast Trainable Projection for Robust Fine-tuning. - Shengpu Tang, Jenna Wiens:
Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation. - Nimrah Mustafa, Aleksandar Bojchevski, Rebekka Burkholz:
Are GATs Out of Balance? - Zhongang Cai, Wanqi Yin, Ailing Zeng, Chen Wei, Qingping Sun, Wang Yanjun, Hui En Pang, Haiyi Mei, Mingyuan Zhang, Lei Zhang, Chen Change Loy, Lei Yang, Ziwei Liu:
SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation. - Dorian Baudry, Fabien Pesquerel, Rémy Degenne, Odalric-Ambrym Maillard:
Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic Bandits. - Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer:
SHAP-IQ: Unified Approximation of any-order Shapley Interactions. - Tyler LaBonte, Vidya Muthukumar, Abhishek Kumar:
Towards Last-layer Retraining for Group Robustness with Fewer Annotations. - Zhongli Jiang, Dabao Zhang:
Analysis of Variance of Multiple Causal Networks. - Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov:
Revisiting the Minimalist Approach to Offline Reinforcement Learning. - Saurabh Garg, Amrith Setlur, Zachary C. Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan:
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift. - Arthur Pellegrino, N. Alex Cayco-Gajic, Angus Chadwick:
Low Tensor Rank Learning of Neural Dynamics. - Jinrang Jia, Zhenjia Li, Yifeng Shi:
MonoUNI: A Unified Vehicle and Infrastructure-side Monocular 3D Object Detection Network with Sufficient Depth Clues. - Manjie Xu, Guangyuan Jiang, Wei Liang, Chi Zhang, Yixin Zhu:
Active Reasoning in an Open-World Environment. - Alexander Tyurin, Peter Richtárik:
2Direction: Theoretically Faster Distributed Training with Bidirectional Communication Compression. - Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, Karthik Narasimhan:
Tree of Thoughts: Deliberate Problem Solving with Large Language Models. - Nicolas Keriven, Samuel Vaiter:
What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding. - Hugo Cui, Lenka Zdeborová:
High-dimensional Asymptotics of Denoising Autoencoders. - Jack Lanchantin, Shubham Toshniwal, Jason Weston, Arthur Szlam, Sainbayar Sukhbaatar:
Learning to Reason and Memorize with Self-Notes. - Hengyu Fu, Tianyu Guo, Yu Bai, Song Mei:
What can a Single Attention Layer Learn? A Study Through the Random Features Lens. - Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan:
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. - Susung Hong, Donghoon Ahn, Seungryong Kim:
Debiasing Scores and Prompts of 2D Diffusion for View-consistent Text-to-3D Generation. - Vinod Raman, Unique Subedi, Ambuj Tewari:
On the Learnability of Multilabel Ranking. - Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang:
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network. - Mark D. McDonnell, Dong Gong, Amin Parvaneh, Ehsan Abbasnejad, Anton van den Hengel:
RanPAC: Random Projections and Pre-trained Models for Continual Learning. - Xinyu Sun, Peihao Chen, Jugang Fan, Jian Chen, Thomas H. Li, Mingkui Tan:
FGPrompt: Fine-grained Goal Prompting for Image-goal Navigation. - Yukun Qiu, Guo-Hao Xu, Wei-Shi Zheng:
Inner-Outer Aware Reconstruction Model for Monocular 3D Scene Reconstruction. - Iulia Duta, Giulia Cassarà, Fabrizio Silvestri, Pietro Lió:
Sheaf Hypergraph Networks. - Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang:
f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences. - Zhiqun Zuo, Mahdi Khalili, Xueru Zhang:
Counterfactually Fair Representation. - Riccardo Poiani, Nicole Nobili, Alberto Maria Metelli, Marcello Restelli:
Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach. - Wenxuan Bao, Francesco Pittaluga, Vijay Kumar B. G, Vincent Bindschaedler:
DP-Mix: Mixup-based Data Augmentation for Differentially Private Learning. - Yoni Kasten, Ohad Rahamim, Gal Chechik:
Point Cloud Completion with Pretrained Text-to-Image Diffusion Models. - Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R. Walter:
Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback. - Niranjan Damera Venkata, Chiranjib Bhattacharyya:
Deep Recurrent Optimal Stopping. - Anindya Sarkar, Nathan Jacobs, Yevgeniy Vorobeychik:
A Partially-Supervised Reinforcement Learning Framework for Visual Active Search. - Yong Liu, Chenyu Li, Jianmin Wang, Mingsheng Long:
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors. - Liyuan Liu, Chengyu Dong, Xiaodong Liu, Bin Yu, Jianfeng Gao:
Bridging Discrete and Backpropagation: Straight-Through and Beyond. - Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin A. Raffel:
Distributed Inference and Fine-tuning of Large Language Models Over The Internet. - Jingyuan Sun, Mingxiao Li, Zijiao Chen, Yunhao Zhang, Shaonan Wang, Marie-Francine Moens:
Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities. - Ayush Tewari, Tianwei Yin, George Cazenavette, Semon Rezchikov, Josh Tenenbaum, Frédo Durand, Bill Freeman, Vincent Sitzmann:
Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision. - Tomas Vaskevicius, Lénaïc Chizat:
Computational Guarantees for Doubly Entropic Wasserstein Barycenters. - Yuxin Jia, Youfang Lin, Xinyan Hao, Yan Lin, Shengnan Guo, Huaiyu Wan:
WITRAN: Water-wave Information Transmission and Recurrent Acceleration Network for Long-range Time Series Forecasting. - Matthew Lyon, Paul A. Armitage, Mauricio A. Álvarez:
Spatio-Angular Convolutions for Super-resolution in Diffusion MRI. - Changsheng Lv, Shuai Zhang, Yapeng Tian, Mengshi Qi, Huadong Ma:
Disentangled Counterfactual Learning for Physical Audiovisual Commonsense Reasoning. - Nate Gruver, Samuel Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hötzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson:
Protein Design with Guided Discrete Diffusion. - Lyndon R. Duong, Eero P. Simoncelli, Dmitri B. Chklovskii, David Lipshutz:
Adaptive whitening with fast gain modulation and slow synaptic plasticity. - Dongjin Kim, Woojeong Kim, Suhyun Kim:
Tanh Works Better with Asymmetry. - Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao:
Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning. - Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alexander J. Smola, Xu Sun:
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition. - Jinghan Zhang, Shiqi Chen, Junteng Liu, Junxian He:
Composing Parameter-Efficient Modules with Arithmetic Operation. - Yuyuan Li, Chaochao Chen, Yizhao Zhang, Weiming Liu, Lingjuan Lyu, Xiaolin Zheng, Dan Meng, Jun Wang:
UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition. - Elliott Ash, Naman Goel, Nianyun Li, Claudia Marangon, Peiyao Sun:
WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts. - Evangelia Gergatsouli, Christos Tzamos:
Weitzman's Rule for Pandora's Box with Correlations. - Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola:
Compositional Sculpting of Iterative Generative Processes. - Hatef Otroshi-Shahreza, Sébastien Marcel:
Face Reconstruction from Facial Templates by Learning Latent Space of a Generator Network. - Jiachen Zhao, Tao Yu, Liang An, Yipeng Huang, Fang Deng, Qionghai Dai:
Triangulation Residual Loss for Data-efficient 3D Pose Estimation. - Junmin Zhong, Ruofan Wu, Jennie Si:
A Long N-step Surrogate Stage Reward for Deep Reinforcement Learning. - Chaoqi Chen, Luyao Tang, Yue Huang, Xiaoguang Han, Yizhou Yu:
CODA: Generalizing to Open and Unseen Domains with Compaction and Disambiguation. - Jose Javier Gonzalez Ortiz, John V. Guttag, Adrian V. Dalca:
Scale-Space Hypernetworks for Efficient Biomedical Image Analysis. - Chaoqi Wang, Ziyu Ye, Zhe Feng, Ashwinkumar Badanidiyuru Varadaraja, Haifeng Xu:
Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts. - Masatoshi Uehara, Nathan Kallus, Jason D. Lee, Wen Sun:
Offline Minimax Soft-Q-learning Under Realizability and Partial Coverage. - Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang:
Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption. - Ping Li, Xiaoyun Li:
Smooth Flipping Probability for Differential Private Sign Random Projection Methods. - Yanghao Li, Tongda Xu, Yan Wang, Jingjing Liu, Ya-Qin Zhang:
Idempotent Learned Image Compression with Right-Inverse. - Qi Wang, Yiqin Lv, Yang-He Feng, Zheng Xie, Jincai Huang:
A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm. - Alistair White, Niki Kilbertus, Maximilian Gelbrecht, Niklas Boers:
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints. - Yiding Jiang, J. Zico Kolter, Roberta Raileanu:
On the Importance of Exploration for Generalization in Reinforcement Learning. - Lijia Zhou, Zhen Dai, Frederic Koehler, Nati Srebro:
Uniform Convergence with Square-Root Lipschitz Loss. - Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok:
A Fractional Graph Laplacian Approach to Oversmoothing. - Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury:
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. - Hong Chen, Xin Wang, Yuwei Zhou, Yijian Qin, Chaoyu Guan, Wenwu Zhu:
Joint Data-Task Generation for Auxiliary Learning. - Vinod Raman, Unique Subedi, Ambuj Tewari:
On Proper Learnability between Average- and Worst-case Robustness. - Riccardo Zamboni, Alberto Maria Metelli, Marcello Restelli:
Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning. - Daniel Augusto de Souza, Alexander Nikitin, St John, Magnus Ross, Mauricio A. Álvarez, Marc Peter Deisenroth, João Paulo Pordeus Gomes, Diego Mesquita, César Lincoln C. Mattos:
Thin and deep Gaussian processes. - Kevin Ellis:
Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language. - Anders Vestergaard Nørskov, Alexander Neergaard Zahid, Morten Mørup:
CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion. - Eden Saig, Inbal Talgam-Cohen, Nir Rosenfeld:
Delegated Classification. - Yefei He, Luping Liu, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang:
PTQD: Accurate Post-Training Quantization for Diffusion Models. - Katie Luo, Zhenzhen Liu, Xiangyu Chen, Yurong You, Sagie Benaim, Cheng Perng Phoo, Mark E. Campbell, Wen Sun, Bharath Hariharan, Kilian Q. Weinberger:
Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery. - John P. Dickerson, Seyed A. Esmaeili, Jamie H. Morgenstern, Claire Jie Zhang:
Doubly Constrained Fair Clustering. - Zongsheng Yue, Jianyi Wang, Chen Change Loy:
ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting. - Yanchao Tan, Zihao Zhou, Hang Lv, Weiming Liu, Carl Yang:
WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding. - Yujia Zheng, Kun Zhang:
Generalizing Nonlinear ICA Beyond Structural Sparsity. - Hédi Hadiji, Sarah Sachs, Tim van Erven, Wouter M. Koolen:
Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games. - Xiang Cheng, Bohan Wang, Jingzhao Zhang, Yusong Zhu:
Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions. - Guy Hacohen, Daphna Weinshall:
How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget. - Shenghuan Sun, Gregory M. Goldgof, Atul J. Butte, Ahmed M. Alaa:
Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback. - Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Maria Lupidi, Lucie Charlotte Magister, Pietro Lió, Pietro Barbiero:
Interpretable Graph Networks Formulate Universal Algebra Conjectures. - Xin Li, Dongze Lian, Zhihe Lu, Jiawang Bai, Zhibo Chen, Xinchao Wang:
GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph. - Jiayu Wang, Kang Zhao, Yifeng Ma, Shiwei Zhang, Yingya Zhang, Yujun Shen, Deli Zhao, Jingren Zhou:
FaceComposer: A Unified Model for Versatile Facial Content Creation. - Ganyu Wang, Bin Gu, Qingsong Zhang, Xiang Li, Boyu Wang, Charles X. Ling:
A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning. - Zhengmian Hu, Heng Huang:
Optimization and Bayes: A Trade-off for Overparameterized Neural Networks. - Kanishk Gandhi, Jan-Philipp Fränken, Tobias Gerstenberg, Noah D. Goodman:
Understanding Social Reasoning in Language Models with Language Models. - Edward Raff, James Holt:
Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests. - Basile Confavreux, Poornima Ramesh, Pedro J. Gonçalves, Jakob H. Macke, Tim P. Vogels:
Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference. - Alan Jeffares, Tennison Liu, Jonathan Crabbé, Mihaela van der Schaar:
Joint Training of Deep Ensembles Fails Due to Learner Collusion. - Zih-Yun Chiu, Yi-Lin Tuan, William Yang Wang, Michael C. Yip:
Flexible Attention-Based Multi-Policy Fusion for Efficient Deep Reinforcement Learning. - Yite Wang, Jing Wu, Naira Hovakimyan, Ruoyu Sun:
Balanced Training for Sparse GANs. - Hanyang Zhao, Wenpin Tang, David D. Yao:
Policy Optimization for Continuous Reinforcement Learning. - Zhaoxi Chen, Fangzhou Hong, Haiyi Mei, Guangcong Wang, Lei Yang, Ziwei Liu:
PrimDiffusion: Volumetric Primitives Diffusion for 3D Human Generation. - Weijie Tu, Weijian Deng, Tom Gedeon:
A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP). - Yi-Kai Zhang, Ting-Ji Huang, Yao-Xiang Ding, De-Chuan Zhan, Han-Jia Ye:
Model Spider: Learning to Rank Pre-Trained Models Efficiently. - Georg Bökman, Fredrik Kahl:
Investigating how ReLU-networks encode symmetries. - Angela Zhou:
Optimal and Fair Encouragement Policy Evaluation and Learning. - Yao Ni, Piotr Koniusz:
NICE: NoIse-modulated Consistency rEgularization for Data-Efficient GANs. - Yang Yang, Yuxuan Zhang, Xin Song, Yi Xu:
Not All Out-of-Distribution Data Are Harmful to Open-Set Active Learning. - Rachel Redberg, Antti Koskela, Yu-Xiang Wang:
Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners. - Zhu Wang, Sourav Medya, Sathya N. Ravi:
Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis. - Daiwen Sun, He Huang, Yao Li, Xinqi Gong, Qiwei Ye:
DSR: Dynamical Surface Representation as Implicit Neural Networks for Protein. - Yanbo Chen, Weiwei Liu:
A Theory of Transfer-Based Black-Box Attacks: Explanation and Implications. - Galen Pogoncheff, Jacob Granley, Michael Beyeler:
Explaining V1 Properties with a Biologically Constrained Deep Learning Architecture. - Naman Deep Singh, Francesco Croce, Matthias Hein:
Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models. - Michael Kirchhof, Bálint Mucsányi, Seong Joon Oh, Enkelejda Kasneci:
URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates. - Mingyuan Zhang, Huirong Li, Zhongang Cai, Jiawei Ren, Lei Yang, Ziwei Liu:
FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing. - Huizong Yang, Yuxin Sun, Ganesh Sundaramoorthi, Anthony J. Yezzi:
Stabilizing the Optimization of Neural Signed Distance Functions and Finer Shape Representation. - Matthew Le, Apoorv Vyas, Bowen Shi, Brian Karrer, Leda Sari, Rashel Moritz, Mary Williamson, Vimal Manohar, Yossi Adi, Jay Mahadeokar, Wei-Ning Hsu:
Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale. - Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos:
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method. - Taesik Gong, Yewon Kim, Taeckyung Lee, Sorn Chottananurak, Sung-Ju Lee:
SoTTA: Robust Test-Time Adaptation on Noisy Data Streams. - Qi Zhu, Man Zhou, Jie Huang, Naishan Zheng, Hongzhi Gao, Chongyi Li, Yuan Xu, Feng Zhao:
FouriDown: Factoring Down-Sampling into Shuffling and Superposing. - Hailey Joren, Chirag Nagpal, Katherine A. Heller, Berk Ustun:
Participatory Personalization in Classification. - Vignesh Kothapalli, Tom Tirer, Joan Bruna:
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks. - Alfredo De Goyeneche Macaya, Shreya Ramachandran, Ke Wang, Ekin Karasan, Joseph Y. Cheng, Stella X. Yu, Michael Lustig:
ResoNet: Noise-Trained Physics-Informed MRI Off-Resonance Correction. - Jianqing Zhang, Yang Hua, Jian Cao, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan:
Eliminating Domain Bias for Federated Learning in Representation Space. - Allan Raventós, Mansheej Paul, Feng Chen, Surya Ganguli:
Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression. - Xinyi Hu, Jasper C. H. Lee, Jimmy Ho-Man Lee:
Two-Stage Predict+Optimize for MILPs with Unknown Parameters in Constraints. - Zhiding Liu, Mingyue Cheng, Zhi Li, Zhenya Huang, Qi Liu, Yanhu Xie, Enhong Chen:
Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective. - Junru Zhou, Jiarui Feng, Xiyuan Wang, Muhan Zhang:
Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power. - Lore Goetschalckx, Lakshmi Narasimhan Govindarajan, Alekh Karkada Ashok, Aarit Ahuja, David L. Sheinberg, Thomas Serre:
Computing a human-like reaction time metric from stable recurrent vision models. - Ben Dai, Yixuan Qiu:
ReHLine: Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence. - Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal, Ali Vakilian:
Improved Frequency Estimation Algorithms with and without Predictions. - Rongqing Li, Changsheng Li, Dongchun Ren, Guangyi Chen, Ye Yuan, Guoren Wang:
BCDiff: Bidirectional Consistent Diffusion for Instantaneous Trajectory Prediction. - Yuhang Zhang, Yaqi Li, Lixiong Qin, Xuannan Liu, Weihong Deng:
Leave No Stone Unturned: Mine Extra Knowledge for Imbalanced Facial Expression Recognition. - Tianyu Xie, Cheng Zhang:
ARTree: A Deep Autoregressive Model for Phylogenetic Inference. - Yixuan Xu, Steven Jecmen, Zimeng Song, Fei Fang:
A One-Size-Fits-All Approach to Improving Randomness in Paper Assignment. - Blake Bordelon, Paul Masset, Henry Kuo, Cengiz Pehlevan:
Loss Dynamics of Temporal Difference Reinforcement Learning. - Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Rui Zhang, Li Chen, Xin Zhao, Ji-Rong Wen:
REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths. - Ruizhe Chen, Jianfei Yang, Huimin Xiong, Jianhong Bai, Tianxiang Hu, Jin Hao, Yang Feng, Joey Tianyi Zhou, Jian Wu, Zuozhu Liu:
Fast Model DeBias with Machine Unlearning. - Joe Watson, Sandy H. Huang, Nicolas Heess:
Coherent Soft Imitation Learning. - Waïss Azizian, Franck Iutzeler, Jérôme Malick:
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models. - Meena Jagadeesan, Nikhil Garg, Jacob Steinhardt:
Supply-Side Equilibria in Recommender Systems. - Nina Corvelo Benz, Manuel Rodriguez:
Human-Aligned Calibration for AI-Assisted Decision Making. - Dong Kyum Kim, Jea Kwon, Meeyoung Cha, Chul Lee:
Transformer as a hippocampal memory consolidation model based on NMDAR-inspired nonlinearity. - Yangdi Jiang, Xiaotian Chang, Yi Liu, Lei Ding, Linglong Kong, Bei Jiang:
Gaussian Differential Privacy on Riemannian Manifolds. - Aravind Gollakota, Parikshit Gopalan, Adam R. Klivans, Konstantinos Stavropoulos:
Agnostically Learning Single-Index Models using Omnipredictors. - Lachlan E. MacDonald, Jack Valmadre, Hemanth Saratchandran, Simon Lucey:
On skip connections and normalisation layers in deep optimisation. - Yuedong Yang, Hung-Yueh Chiang, Guihong Li, Diana Marculescu, Radu Marculescu:
Efficient Low-rank Backpropagation for Vision Transformer Adaptation. - Paribesh Regmi, Rui Li:
AdaVAE: Bayesian Structural Adaptation for Variational Autoencoders. - Christian Schilling, Anna Lukina, Emir Demirovic, Kim Guldstrand Larsen:
Safety Verification of Decision-Tree Policies in Continuous Time. - Isaac Reid, Adrian Weller, Krzysztof Marcin Choromanski:
Quasi-Monte Carlo Graph Random Features. - Dihong Jiang, Sun Sun, Yaoliang Yu:
Functional Renyi Differential Privacy for Generative Modeling. - Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszar, Nicholas D. Lane:
FedL2P: Federated Learning to Personalize. - Zhaoyu Li, Jinpei Guo, Yuhe Jiang, Xujie Si:
Learning Reliable Logical Rules with SATNet. - Yuki Wang, Gonzalo Gonzalez-Pumariega, Yash Sharma, Sanjiban Choudhury:
Demo2Code: From Summarizing Demonstrations to Synthesizing Code via Extended Chain-of-Thought. - Róbert Busa-Fekete, Heejin Choi, Travis Dick, Claudio Gentile, Andrés Muñoz Medina:
Easy Learning from Label Proportions. - Jiaxin Lu, Yifan Sun, Qixing Huang:
Jigsaw: Learning to Assemble Multiple Fractured Objects. - Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Mirco Mutti:
Persuading Farsighted Receivers in MDPs: the Power of Honesty. - Ryan Theisen, Hyunsuk Kim, Yaoqing Yang, Liam Hodgkinson, Michael W. Mahoney:
When are ensembles really effective? - Haizhou Shi, Hao Wang:
A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm. - Qi-Wei Wang, Da-Wei Zhou, Yi-Kai Zhang, De-Chuan Zhan, Han-Jia Ye:
Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration. - Xiaomeng Hu, Pin-Yu Chen, Tsung-Yi Ho:
RADAR: Robust AI-Text Detection via Adversarial Learning. - Tao Fang, Qian Zheng, Gang Pan:
Alleviating the Semantic Gap for Generalized fMRI-to-Image Reconstruction. - Changhyeon Lee, Seulki Lee:
Softmax Output Approximation for Activation Memory-Efficient Training of Attention-based Networks. - Marc Marone, Benjamin Van Durme:
Data Portraits: Recording Foundation Model Training Data. - Bingrui Li, Jianfei Chen, Jun Zhu:
Memory Efficient Optimizers with 4-bit States. - Eric Eaton, Marcel Hussing, Michael Kearns, Jessica Sorrell:
Replicable Reinforcement Learning. - Baohao Liao, Shaomu Tan, Christof Monz:
Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning. - Jinxin Liu, Hongyin Zhang, Zifeng Zhuang, Yachen Kang, Donglin Wang, Bin Wang:
Design from Policies: Conservative Test-Time Adaptation for Offline Policy Optimization. - Qihang Fan, Huaibo Huang, Xiaoqiang Zhou, Ran He:
Lightweight Vision Transformer with Bidirectional Interaction. - Xinyu Ma, Xu Chu, Yasha Wang, Yang Lin, Junfeng Zhao, Liantao Ma, Wenwu Zhu:
Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications. - Jung Yeon Park, Lawson L. S. Wong, Robin Walters:
Modeling Dynamics over Meshes with Gauge Equivariant Nonlinear Message Passing. - Antonio Norelli, Marco Fumero, Valentino Maiorca, Luca Moschella, Emanuele Rodolà, Francesco Locatello:
ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training. - Ting Wei Li, Qiaozhu Mei, Jiaqi Ma:
A Metadata-Driven Approach to Understand Graph Neural Networks. - Aiwen Xu, Yuchen Hou, Cristopher Niell, Michael Beyeler:
Multimodal Deep Learning Model Unveils Behavioral Dynamics of V1 Activity in Freely Moving Mice. - Marco Bagatella, Georg Martius:
Goal-conditioned Offline Planning from Curious Exploration. - Jinhyuk Lee, Zhuyun Dai, Sai Meher Karthik Duddu, Tao Lei, Iftekhar Naim, Ming-Wei Chang, Vincent Zhao:
Rethinking the Role of Token Retrieval in Multi-Vector Retrieval. - Andrew Wagenmaker, Guanya Shi, Kevin G. Jamieson:
Optimal Exploration for Model-Based RL in Nonlinear Systems. - Zizhao Wang, Jiaheng Hu, Peter Stone, Roberto Martín-Martín:
ELDEN: Exploration via Local Dependencies. - Gang Li, Wei Tong, Tianbao Yang:
Maximization of Average Precision for Deep Learning with Adversarial Ranking Robustness. - Peng Jin, Yang Wu, Yanbo Fan, Zhongqian Sun, Wei Yang, Li Yuan:
Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs. - Logan M. Bhamidipaty, Tommy Bruzzese, Caryn Tran, Rami Ratl Mrad, Maxinder S. Kanwal:
DynaDojo: An Extensible Platform for Benchmarking Scaling in Dynamical System Identification. - Siyuan Xu, Minghui Zhu:
Online Constrained Meta-Learning: Provable Guarantees for Generalization. - Taiji Suzuki, Denny Wu, Atsushi Nitanda:
Mean-field Langevin dynamics: Time-space discretization, stochastic gradient, and variance reduction. - Junliang Li, Yajun Yang, Qinghua Hu, Xin Wang, Hong Gao:
Public Opinion Field Effect Fusion in Representation Learning for Trending Topics Diffusion. - Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley Llorens:
Distributional Pareto-Optimal Multi-Objective Reinforcement Learning. - Xinyi Wang, Wanrong Zhu, Michael Saxon, Mark Steyvers, William Yang Wang:
Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning. - Ruiyuan Kang, Tingting Mu, Panagiotis Liatsis, Dimitrios C. Kyritsis:
Physics-Driven ML-Based Modelling for Correcting Inverse Estimation. - Zichang Liu, Zhaozhuo Xu, Benjamin Coleman, Anshumali Shrivastava:
One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning. - Patrik Róbert Gerber, Tianze Jiang, Yury Polyanskiy, Rui Sun:
Kernel-Based Tests for Likelihood-Free Hypothesis Testing. - Tanya Marwah, Ashwini Pokle, J. Zico Kolter, Zachary C. Lipton, Jianfeng Lu, Andrej Risteski:
Deep Equilibrium Based Neural Operators for Steady-State PDEs. - Mengzhao Wang, Lingwei Lv, Xiaoliang Xu, Yuxiang Wang, Qiang Yue, Jiongkang Ni:
An Efficient and Robust Framework for Approximate Nearest Neighbor Search with Attribute Constraint. - Haixin Wang, Xinlong Yang, Jianlong Chang, Dian Jin, Jinan Sun, Shikun Zhang, Xiao Luo, Qi Tian:
Parameter-efficient Tuning of Large-scale Multimodal Foundation Model. - Yifei Wang, Liangchen Li, Jiansheng Yang, Zhouchen Lin, Yisen Wang:
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective. - Hammaad Adam, Fan Yin, Huibin Hu, Neil A. Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke:
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. - Ryan M. Rogers, Gennady Samorodnitsky, Zhiwei Steven Wu, Aaditya Ramdas:
Adaptive Privacy Composition for Accuracy-first Mechanisms. - Xiaohan Wang, Yuehu Liu, Xinhang Song, Beibei Wang, Shuqiang Jiang:
CaMP: Causal Multi-policy Planning for Interactive Navigation in Multi-room Scenes. - Ximing Xing, Chuang Wang, Haitao Zhou, Jing Zhang, Qian Yu, Dong Xu:
DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models. - Yuchao Gu, Xintao Wang, Jay Zhangjie Wu, Yujun Shi, Yunpeng Chen, Zihan Fan, Wuyou Xiao, Rui Zhao, Shuning Chang, Weijia Wu, Yixiao Ge, Ying Shan, Mike Zheng Shou:
Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models. - Jiazheng Xu, Xiao Liu, Yuchen Wu, Yuxuan Tong, Qinkai Li, Ming Ding, Jie Tang, Yuxiao Dong:
ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation. - Ildus Sadrtdinov, Dmitrii Pozdeev, Dmitry P. Vetrov, Ekaterina Lobacheva:
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning. - Licong Lin, Mufang Ying, Suvrojit Ghosh, Koulik Khamaru, Cun-Hui Zhang:
Statistical Limits of Adaptive Linear Models: Low-Dimensional Estimation and Inference. - Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun:
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs. - Ying Wang, Tim G. J. Rudner, Andrew Gordon Wilson:
Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution. - Radoslav Dimitrov, Zeyang Zhao, Ralph Abboud, Ismail Ilkan Ceylan:
PlanE: Representation Learning over Planar Graphs. - Ziyi Huang, Henry Lam, Amirhossein Meisami, Haofeng Zhang:
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework. - Zineng Tang, Ziyi Yang, Chenguang Zhu, Michael Zeng, Mohit Bansal:
Any-to-Any Generation via Composable Diffusion. - Yifan Pu, Weicong Liang, Yiduo Hao, Yuhui Yuan, Yukang Yang, Chao Zhang, Han Hu, Gao Huang:
Rank-DETR for High Quality Object Detection. - Kun Huang, Xin Guo, Meng Wang:
Towards Efficient Pre-Trained Language Model via Feature Correlation Distillation. - Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang:
Simple and Asymmetric Graph Contrastive Learning without Augmentations. - Tahseen Rabbani, Marco Bornstein, Furong Huang:
Large-Scale Distributed Learning via Private On-Device LSH. - Cai Zhou, Xiyuan Wang, Muhan Zhang:
Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes. - Petar Bevanda, Max Beier, Armin Lederer, Stefan Sosnowski, Eyke Hüllermeier, Sandra Hirche:
Koopman Kernel Regression. - Dave Epstein, Allan Jabri, Ben Poole, Alexei A. Efros, Aleksander Holynski:
Diffusion Self-Guidance for Controllable Image Generation. - Mariia Seleznova, Dana Weitzner, Raja Giryes, Gitta Kutyniok, Hung-Hsu Chou:
Neural (Tangent Kernel) Collapse. - Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar:
Fast Optimal Locally Private Mean Estimation via Random Projections. - Sara Sangalli, Ertunc Erdil, Ender Konukoglu:
Expert load matters: operating networks at high accuracy and low manual effort. - Qian Huang, Hongyu Ren, Peng Chen, Gregor Krzmanc, Daniel Zeng, Percy Liang, Jure Leskovec:
PRODIGY: Enabling In-context Learning Over Graphs. - Arthur Conmy, Augustine N. Mavor-Parker, Aengus Lynch, Stefan Heimersheim, Adrià Garriga-Alonso:
Towards Automated Circuit Discovery for Mechanistic Interpretability. - Hongcheng Wang, Andy Guan Hong Chen, Xiaoqi Li, Mingdong Wu, Hao Dong:
Find What You Want: Learning Demand-conditioned Object Attribute Space for Demand-driven Navigation. - Ioannis Anagnostides, Ioannis Panageas, Gabriele Farina, Tuomas Sandholm:
On the Convergence of No-Regret Learning Dynamics in Time-Varying Games. - Ibrahim M. Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer:
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. - Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron:
Expressive Sign Equivariant Networks for Spectral Geometric Learning. - Anatol Garioud, Nicolas Gonthier, Loïc Landrieu, Apolline De Wit, Marion Valette, Marc Poupée, Sébastien Giordano, Boris Wattrelos:
FLAIR : a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery. - Nikita Tsoy, Nikola Konstantinov:
Strategic Data Sharing between Competitors. - Alexander Tyurin, Peter Richtárik:
Optimal Time Complexities of Parallel Stochastic Optimization Methods Under a Fixed Computation Model. - Marc Jourdan, Rémy Degenne, Emilie Kaufmann:
An ε-Best-Arm Identification Algorithm for Fixed-Confidence and Beyond. - Haobo Wang, Yiwen Dong, Ruixuan Xiao, Fei Huang, Gang Chen, Junbo Zhao:
Debiased and Denoised Entity Recognition from Distant Supervision. - Xin Yuan, Pedro Savarese, Michael Maire:
Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation. - Ishaan Gulrajani, Tatsunori B. Hashimoto:
Likelihood-Based Diffusion Language Models. - Gongfan Fang, Xinyin Ma, Xinchao Wang:
Structural Pruning for Diffusion Models. - Qining Zhang, Lei Ying:
Fast and Regret Optimal Best Arm Identification: Fundamental Limits and Low-Complexity Algorithms. - Haggai Agmon, Yoram Burak:
Simultaneous embedding of multiple attractor manifolds in a recurrent neural network using constrained gradient optimization. - Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli:
Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization. - Po-An Wang, Ruo-Chun Tzeng, Alexandre Proutière:
Best Arm Identification with Fixed Budget: A Large Deviation Perspective. - Zaixi Zhang, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu:
Full-Atom Protein Pocket Design via Iterative Refinement. - Jonas Wildberger, Maximilian Dax, Simon Buchholz, Stephen R. Green, Jakob H. Macke, Bernhard Schölkopf:
Flow Matching for Scalable Simulation-Based Inference. - Panagiotis Misiakos, Chris Wendler, Markus Püschel:
Learning DAGs from Data with Few Root Causes. - Pengfei Li, Jianyi Yang, Adam Wierman, Shaolei Ren:
Robust Learning for Smoothed Online Convex Optimization with Feedback Delay. - Amelie Royer, Tijmen Blankevoort, Babak Ehteshami Bejnordi:
Scalarization for Multi-Task and Multi-Domain Learning at Scale. - Adam Li, Amin Jaber, Elias Bareinboim:
Causal discovery from observational and interventional data across multiple environments. - Pawel Czyz, Frederic Grabowski, Julia E. Vogt, Niko Beerenwinkel, Alexander Marx:
Beyond Normal: On the Evaluation of Mutual Information Estimators. - Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian:
Structured Semidefinite Programming for Recovering Structured Preconditioners. - Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang:
Certifiably Robust Graph Contrastive Learning. - Zuhao Yang, Yingfang Yuan, Yang Xu, Shuo Zhan, Huajun Bai, Kefan Chen:
FACE: Evaluating Natural Language Generation with Fourier Analysis of Cross-Entropy. - Yunhao Ge, Hong-Xing Yu, Cheng Zhao, Yuliang Guo, Xinyu Huang, Liu Ren, Laurent Itti, Jiajun Wu:
3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D Detection. - Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio:
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. - Yuanzhi Wang, Yong Li, Zhen Cui:
Incomplete Multimodality-Diffused Emotion Recognition. - Zhekai Du, Jingjing Li:
Diffusion-Based Probabilistic Uncertainty Estimation for Active Domain Adaptation. - Suresh Kumar Amalapuram, Sumohana S. Channappayya, Bheemarjuna Reddy Tamma:
Augmented Memory Replay-based Continual Learning Approaches for Network Intrusion Detection. - Alvin Heng, Harold Soh:
Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models. - Tianhang Cheng, Wei-Chiu Ma, Kaiyu Guan, Antonio Torralba, Shenlong Wang:
Structure from Duplicates: Neural Inverse Graphics from a Pile of Objects. - Shentong Mo, Bhiksha Raj:
Weakly-Supervised Audio-Visual Segmentation. - Ang Li, Yifei Wang, Yiwen Guo, Yisen Wang:
Adversarial Examples Are Not Real Features. - Hao Yan, Chaozhuo Li, Ruosong Long, Chao Yan, Jianan Zhao, Wenwen Zhuang, Jun Yin, Peiyan Zhang, Weihao Han, Hao Sun, Weiwei Deng, Qi Zhang, Lichao Sun, Xing Xie, Senzhang Wang:
A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking. - Fabian Spaeh, Alina Ene:
Online Ad Allocation with Predictions. - Shunya Minami, Kenji Fukumizu, Yoshihiro Hayashi, Ryo Yoshida:
Transfer Learning with Affine Model Transformation. - Hui En Pang, Zhongang Cai, Lei Yang, Qingyi Tao, Zhonghua Wu, Tianwei Zhang, Ziwei Liu:
Towards Robust and Expressive Whole-body Human Pose and Shape Estimation. - Ting Li, Jianguo Li, Zhanxing Zhu:
Neural Lad: A Neural Latent Dynamics Framework for Times Series Modeling. - Huiyang Shao, Qianqian Xu, Zhiyong Yang, Peisong Wen, Peifeng Gao, Qingming Huang:
Weighted ROC Curve in Cost Space: Extending AUC to Cost-Sensitive Learning. - Kiarash Banihashem, Leyla Biabani, Samira Goudarzi, MohammadTaghi Hajiaghayi, Peyman Jabbarzade, Morteza Monemizadeh:
Dynamic Non-monotone Submodular Maximization. - Yanwu Xu, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou:
Semi-Implicit Denoising Diffusion Models (SIDDMs). - Maksim Zhdanov, Nico Hoffmann, Gabriele Cesa:
Implicit Convolutional Kernels for Steerable CNNs. - Jui-Nan Yen, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh:
Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization. - Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu:
Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective. - Max W. Y. Lam, Qiao Tian, Tang Li, Zongyu Yin, Siyuan Feng, Ming Tu, Yuliang Ji, Rui Xia, Mingbo Ma, Xuchen Song, Jitong Chen, Yuping Wang, Yuxuan Wang:
Efficient Neural Music Generation. - Rui Jiao, Wenbing Huang, Peijia Lin, Jiaqi Han, Pin Chen, Yutong Lu, Yang Liu:
Crystal Structure Prediction by Joint Equivariant Diffusion. - Polina Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Shanmukha Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson:
Understanding the detrimental class-level effects of data augmentation. - Liang Zhang, Junchi Yang, Amin Karbasi, Niao He:
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization. - Mihir Prabhudesai, Tsung-Wei Ke, Alexander C. Li, Deepak Pathak, Katerina Fragkiadaki:
Test-time Adaptation of Discriminative Models via Diffusion Generative Feedback. - Kha-Dinh Luong, Ambuj K. Singh:
Fragment-based Pretraining and Finetuning on Molecular Graphs. - Yuzhe Lu, Yilong Qin, Runtian Zhai, Andrew Shen, Ketong Chen, Zhenlin Wang, Soheil Kolouri, Simon Stepputtis, Joseph Campbell, Katia P. Sycara:
Characterizing Out-of-Distribution Error via Optimal Transport. - Pengfei Wei, Lingdong Kong, Xinghua Qu, Yi Ren, Zhiqiang Xu, Jing Jiang, Xiang Yin:
Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective. - Peter Hase, Mohit Bansal, Been Kim, Asma Ghandeharioun:
Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge Editing in Language Models. - Agustinus Kristiadi, Felix Dangel, Philipp Hennig:
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization. - Gyeongsik Moon, Shunsuke Saito, Weipeng Xu, Rohan Joshi, Julia Buffalini, Harley Bellan, Nicholas Rosen, Jesse Richardson, Mallorie Mize, Philippe de Bree, Tomas Simon, Bo Peng, Shubham Garg, Kevyn McPhail, Takaaki Shiratori:
A Dataset of Relighted 3D Interacting Hands. - Zhendong Chu, Nan Wang, Hongning Wang:
Multi-Objective Intrinsic Reward Learning for Conversational Recommender Systems. - Chunlin Sun, Linyu Liu, Xiaocheng Li:
Predict-then-Calibrate: A New Perspective of Robust Contextual LP. - Shih-Cheng Huang, Zepeng Huo, Ethan Steinberg, Chia-Chun Chiang, Curtis P. Langlotz, Matthew P. Lungren, Serena Yeung, Nigam Shah, Jason Alan Fries:
INSPECT: A Multimodal Dataset for Patient Outcome Prediction of Pulmonary Embolisms. - Yuanhan Zhang, Kaiyang Zhou, Ziwei Liu:
What Makes Good Examples for Visual In-Context Learning? - Yongrui Chen, Shenyu Zhang, Guilin Qi, Xinnan Guo:
Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsing. - Aniket Murhekar, Zhuowen Yuan, Bhaskar Ray Chaudhury, Bo Li, Ruta Mehta:
Incentives in Federated Learning: Equilibria, Dynamics, and Mechanisms for Welfare Maximization. - Mohammad Mozaffari, Sikan Li, Zhao Zhang, Maryam Mehri Dehnavi:
MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates. - Kangyang Luo, Shuai Wang, Yexuan Fu, Xiang Li, Yunshi Lan, Ming Gao:
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning. - Zeyu Zhang, Robert Pless, Nadia Shakoor, Austin Carnahan, Abby Stylianou:
SG×P : A Sorghum Genotype × Phenotype Prediction Dataset and Benchmark. - Kaiwen Zha, Peng Cao, Jeany Son, Yuzhe Yang, Dina Katabi:
Rank-N-Contrast: Learning Continuous Representations for Regression. - Zhiyao Zhou, Sheng Zhou, Bochao Mao, Xuanyi Zhou, Jiawei Chen, Qiaoyu Tan, Daochen Zha, Yan Feng, Chun Chen, Can Wang:
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning. - Chang Deng, Kevin Bello, Pradeep Ravikumar, Bryon Aragam:
Global Optimality in Bivariate Gradient-based DAG Learning. - Austin Xu, Andrew D. McRae, Jingyan Wang, Mark A. Davenport, Ashwin Pananjady:
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning. - Subba Reddy Oota, Manish Gupta, Mariya Toneva:
Joint processing of linguistic properties in brains and language models. - Yunho Jin, Chun-Feng Wu, David Brooks, Gu-Yeon Wei:
S3: Increasing GPU Utilization during Generative Inference for Higher Throughput. - Xiangzhi Chen, Le Wu, Fei Liu, Lei Chen, Kun Zhang, Richang Hong, Meng Wang:
Disentangling Cognitive Diagnosis with Limited Exercise Labels. - Khai Nguyen, Nhat Ho:
Energy-Based Sliced Wasserstein Distance. - Xiuhong Lin, Changjie Qiu, Zhipeng Cai, Siqi Shen, Yu Zang, Weiquan Liu, Xuesheng Bian, Matthias Müller, Cheng Wang:
E2PNet: Event to Point Cloud Registration with Spatio-Temporal Representation Learning. - Soham Deshmukh, Benjamin Elizalde, Rita Singh, Huaming Wang:
Pengi: An Audio Language Model for Audio Tasks. - Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He:
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift. - Vijay Veerabadran, Srinivas Ravishankar, Yuan Tang, Ritik Raina, Virginia de Sa:
Adaptive recurrent vision performs zero-shot computation scaling to unseen difficulty levels. - Ming Hu, Lin Wang, Siyuan Yan, Don Ma, Qingli Ren, Peng Xia, Wei Feng, Peibo Duan, Lie Ju, Zongyuan Ge:
NurViD: A Large Expert-Level Video Database for Nursing Procedure Activity Understanding. - Dario Paccagnan, Marco C. Campi, Simone Garatti:
The Pick-to-Learn Algorithm: Empowering Compression for Tight Generalization Bounds and Improved Post-training Performance. - Jing Li, Quanxue Gao, Qianqian Wang, Ming Yang, Wei Xia:
Orthogonal Non-negative Tensor Factorization based Multi-view Clustering. - Md. Wahiduzzaman Khan, Hongwei Sheng, Hu Zhang, Heming Du, Sen Wang, Minas Theodore Coroneo, Farshid Hajati, Sahar Shariflou, Michael Kalloniatis, Jack Phu, Ashish Agar, Zi Huang, S. Mojtaba Golzan, Xin Yu:
RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation. - Weixi Feng, Wanrong Zhu, Tsu-Jui Fu, Varun Jampani, Arjun R. Akula, Xuehai He, Sugato Basu, Xin Eric Wang, William Yang Wang:
LayoutGPT: Compositional Visual Planning and Generation with Large Language Models. - Haoru Tan, Sitong Wu, Fei Du, Yukang Chen, Zhibin Wang, Fan Wang, Xiaojuan Qi:
Data Pruning via Moving-one-Sample-out. - Volkan Cevher, Ashok Cutkosky, Ali Kavis, Georgios Piliouras, Stratis Skoulakis, Luca Viano:
Alternation makes the adversary weaker in two-player games. - Cian Eastwood, Shashank Singh, Andrei Liviu Nicolicioiu, Marin Vlastelica Pogancic, Julius von Kügelgen, Bernhard Schölkopf:
Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features. - Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck:
A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints. - Kim Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, Klaus-Robert Müller, Paolo Stornati, Pan Kessel, Shinichi Nakajima:
Physics-Informed Bayesian Optimization of Variational Quantum Circuits. - Naishan Zheng, Man Zhou, Chong Zhou, Chen Change Loy:
Rubik's Cube: High-Order Channel Interactions with a Hierarchical Receptive Field. - Ruo-Chun Tzeng, Po-An Wang, Alexandre Proutière, Chi-Jen Lu:
Closing the Computational-Statistical Gap in Best Arm Identification for Combinatorial Semi-bandits. - Ziniu Li, Tian Xu, Zeyu Qin, Yang Yu, Zhi-Quan Luo:
Imitation Learning from Imperfection: Theoretical Justifications and Algorithms. - Yuki Kawana, Tatsuya Harada:
Detection Based Part-level Articulated Object Reconstruction from Single RGBD Image. - Zhuo Huang, Li Shen, Jun Yu, Bo Han, Tongliang Liu:
FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning. - Shreyas Malakarjun Patil, Loizos Michael, Constantine Dovrolis:
Neural Sculpting: Uncovering hierarchically modular task structure in neural networks through pruning and network analysis. - Yueh-Hua Wu, Xiaolong Wang, Masashi Hamaya:
Elastic Decision Transformer. - Evelyn Xiao-Yue Gong, Mark Sellke:
Asymptotically Optimal Quantile Pure Exploration for Infinite-Armed Bandits. - Jinwoo Kim, Dat Nguyen, Ayhan Suleymanzade, Hyeokjun An, Seunghoon Hong:
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance. - Bahar Taskesen, Dan A. Iancu, Çagil Koçyigit, Daniel Kuhn:
Distributionally Robust Linear Quadratic Control. - Sayan Bhattacharya, Martín Costa, Silvio Lattanzi, Nikos Parotsidis:
Fully Dynamic k-Clustering in Õ(k) Update Time. - Lihe Yang, Xiaogang Xu, Bingyi Kang, Yinghuan Shi, Hengshuang Zhao:
FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models. - Zhuoqun Huang, Neil G. Marchant, Keane Lucas, Lujo Bauer, Olga Ohrimenko, Benjamin I. P. Rubinstein:
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion. - Kunjal Panchal, Sunav Choudhary, Nisarg Parikh, Lijun Zhang, Hui Guan:
Flow: Per-instance Personalized Federated Learning. - Jianfei Yang, He Huang, Yunjiao Zhou, Xinyan Chen, Yuecong Xu, Shenghai Yuan, Han Zou, Chris Xiaoxuan Lu, Lihua Xie:
MM-Fi: Multi-Modal Non-Intrusive 4D Human Dataset for Versatile Wireless Sensing. - Zhen Zhang, Bingqiao Luo, Shengliang Lu, Bingsheng He:
Live Graph Lab: Towards Open, Dynamic and Real Transaction Graphs with NFT. - Yazhou Zhang, Yang Yu, Qing Guo, Benyou Wang, Dongming Zhao, Sagar Uprety, Dawei Song, Qiuchi Li, Jing Qin:
CMMA: Benchmarking Multi-Affection Detection in Chinese Multi-Modal Conversations. - Joey Hejna, Dorsa Sadigh:
Inverse Preference Learning: Preference-based RL without a Reward Function. - Rajarshi Saha, Varun Srivastava, Mert Pilanci:
Matrix Compression via Randomized Low Rank and Low Precision Factorization. - Huijie Wang, Tianyu Li, Yang Li, Li Chen, Chonghao Sima, Zhenbo Liu, Bangjun Wang, Peijin Jia, Yuting Wang, Shengyin Jiang, Feng Wen, Hang Xu, Ping Luo, Junchi Yan, Wei Zhang, Hongyang Li:
OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mapping. - Siqiao Xue, Yan Wang, Zhixuan Chu, Xiaoming Shi, Caigao Jiang, Hongyan Hao, Gangwei Jiang, Xiaoyun Feng, James Zhang, Jun Zhou:
Prompt-augmented Temporal Point Process for Streaming Event Sequence. - Robert Allison, Anthony Stephenson, Samuel F, Edward O. Pyzer-Knapp:
Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression. - Nikita Gushchin, Alexander Kolesov, Petr Mokrov, Polina Karpikova, Andrei Spiridonov, Evgeny Burnaev, Alexander Korotin:
Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark. - Jiaming Ji, Borong Zhang, Jiayi Zhou, Xuehai Pan, Weidong Huang, Ruiyang Sun, Yiran Geng, Yifan Zhong, Josef Dai, Yaodong Yang:
Safety Gymnasium: A Unified Safe Reinforcement Learning Benchmark. - Bhaskar Mukhoty, Velibor Bojkovic, William de Vazelhes, Xiaohan Zhao, Giulia De Masi, Huan Xiong, Bin Gu:
Direct Training of SNN using Local Zeroth Order Method. - Yu Wang, Zhun Zhong, Pengchong Qiao, Xuxin Cheng, Xiawu Zheng, Chang Liu, Nicu Sebe, Rongrong Ji, Jie Chen:
Discover and Align Taxonomic Context Priors for Open-world Semi-Supervised Learning. - Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes S. Otterbach, Martin Genzel:
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models. - Xiao Ma, Bingyi Kang, Zhongwen Xu, Min Lin, Shuicheng Yan:
Mutual Information Regularized Offline Reinforcement Learning. - Franziska Boenisch, Christopher Mühl, Adam Dziedzic, Roy Rinberg, Nicolas Papernot:
Have it your way: Individualized Privacy Assignment for DP-SGD. - Ran Ran, Nuo Xu, Tao Liu, Wei Wang, Gang Quan, Wujie Wen:
Penguin: Parallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference. - Fan Feng, Sara Magliacane:
Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning. - Tao Zhang, Yaowu Zhang, Tingyou Zhou:
Statistical Insights into HSIC in High Dimensions. - Waverly Wei, Xinwei Ma, Jingshen Wang:
Fair Adaptive Experiments. - Qiaozi Gao, Govind Thattai, Suhaila Shakiah, Xiaofeng Gao, Shreyas Pansare, Vasu Sharma, Gaurav S. Sukhatme, Hangjie Shi, Bofei Yang, Desheng Zhang, Lucy Hu, Karthika Arumugam, Shui Hu, Matthew Wen, Dinakar Guthy, Shunan Chung, Rohan Khanna, Osman Ipek, Leslie Ball, Kate Bland, Heather Rocker, Michael Johnston, Reza Ghanadan, Dilek Hakkani-Tur, Prem Natarajan:
Alexa Arena: A User-Centric Interactive Platform for Embodied AI. - Abhineet Agarwal, Anish Agarwal, Suhas Vijaykumar:
Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions. - Hyemi Jang, Junsung Park, Dahuin Jung, Jaihyun Lew, Ho Bae, Sungroh Yoon:
PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising. - Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee:
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models. - Taoli Cheng, Aaron C. Courville:
Versatile Energy-Based Probabilistic Models for High Energy Physics. - Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
User-Level Differential Privacy With Few Examples Per User. - Ava Pun, Gary Sun, Jingkang Wang, Yun Chen, Ze Yang, Sivabalan Manivasagam, Wei-Chiu Ma, Raquel Urtasun:
Neural Lighting Simulation for Urban Scenes. - Jesse Mu, Xiang Li, Noah D. Goodman:
Learning to Compress Prompts with Gist Tokens. - Feynman T. Liang, Liam Hodgkinson, Michael W. Mahoney:
A Heavy-Tailed Algebra for Probabilistic Programming. - Lu Qi, Jason Kuen, Weidong Guo, Jiuxiang Gu, Zhe Lin, Bo Du, Yu Xu, Ming-Hsuan Yang:
AIMS: All-Inclusive Multi-Level Segmentation for Anything. - Yashaswini Murthy, Mehrdad Moharrami, R. Srikant:
Performance Bounds for Policy-Based Average Reward Reinforcement Learning Algorithms. - Minyang Hu, Hong Chang, Zong Guo, Bingpeng Ma, Shiguang Shan, Xilin Chen:
Understanding Few-Shot Learning: Measuring Task Relatedness and Adaptation Difficulty via Attributes. - Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Kartik Ahuja, Vijay Arya:
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning. - Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter:
Quantification of Uncertainty with Adversarial Models. - Qijian Zhang, Junhui Hou, Yohanes Yudhi Adikusuma, Wenping Wang, Ying He:
NeuroGF: A Neural Representation for Fast Geodesic Distance and Path Queries. - Steve Hanneke, Shay Moran, Jonathan Shafer:
A Trichotomy for Transductive Online Learning. - Shangshang Yang, Xiaoshan Yu, Ye Tian, Xueming Yan, Haiping Ma, Xingyi Zhang:
Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing. - Kwangjun Ahn, Sébastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang:
Learning threshold neurons via edge of stability. - Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong:
k-Means Clustering with Distance-Based Privacy. - Yinghao Aaron Li, Cong Han, Vinay S. Raghavan, Gavin Mischler, Nima Mesgarani:
StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models. - Nate Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson:
Large Language Models Are Zero-Shot Time Series Forecasters. - Kulin Shah, Sitan Chen, Adam R. Klivans:
Learning Mixtures of Gaussians Using the DDPM Objective. - Zhihao Wu, Zhao Zhang, Jicong Fan:
Graph Convolutional Kernel Machine versus Graph Convolutional Networks. - Ilias Diakonikolas, Sushrut Karmalkar, Jongho Park, Christos Tzamos:
First Order Stochastic Optimization with Oblivious Noise. - Zitong Sam Chen, Chau Pham, Siqi Wang, Michael Doron, Nikita Moshkov, Bryan A. Plummer, Juan C. Caicedo:
CHAMMI: A benchmark for channel-adaptive models in microscopy imaging. - Xingyue Huang, Miguel Romero, Ismail Ilkan Ceylan, Pablo Barceló:
A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs. - Shu Yu Tew, Mario Boley, Daniel F. Schmidt:
Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization. - Xueyan Zou, Jianwei Yang, Hao Zhang, Feng Li, Linjie Li, Jianfeng Wang, Lijuan Wang, Jianfeng Gao, Yong Jae Lee:
Segment Everything Everywhere All at Once. - Xutao Wang, Hanting Chen, Tianyu Guo, Yunhe Wang:
PUe: Biased Positive-Unlabeled Learning Enhancement by Causal Inference. - Liliang Ren, Yang Liu, Shuohang Wang, Yichong Xu, Chenguang Zhu, ChengXiang Zhai:
Sparse Modular Activation for Efficient Sequence Modeling. - Patrick Emami, Abhijeet Sahu, Peter Graf:
BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting. - Steven Adriaensen, Herilalaina Rakotoarison, Samuel Müller, Frank Hutter:
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks. - Zeyu Zhang, Yi Su, Hui Yuan, Yiran Wu, Rishab Balasubramanian, Qingyun Wu, Huazheng Wang, Mengdi Wang:
Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective. - Dohyeong Kim, Kyungjae Lee, Songhwai Oh:
Trust Region-Based Safe Distributional Reinforcement Learning for Multiple Constraints. - Ryan Thompson, Amir Dezfouli, Robert Kohn:
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks. - Sagar Vaze, Andrea Vedaldi, Andrew Zisserman:
No Representation Rules Them All in Category Discovery. - Juan M. Cardenas, Ben Adcock, Nick C. Dexter:
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions. - Jiahui Li, Kun Kuang, Baoxiang Wang, Xingchen Li, Fei Wu, Jun Xiao, Long Chen:
Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning. - Maofeng Tang, Andrei Cozma, Konstantinos Georgiou, Hairong Qi:
Cross-Scale MAE: A Tale of Multiscale Exploitation in Remote Sensing. - Biao Jiang, Xin Chen, Wen Liu, Jingyi Yu, Gang Yu, Tao Chen:
MotionGPT: Human Motion as a Foreign Language. - Dylan J. Foster, Noah Golowich, Jian Qian, Alexander Rakhlin, Ayush Sekhari:
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient. - Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar:
FlowPG: Action-constrained Policy Gradient with Normalizing Flows. - Hisham Husain, Vu Nguyen, Anton van den Hengel:
Distributionally Robust Bayesian Optimization with φ-divergences. - Sihan Zeng, Thinh T. Doan, Justin Romberg:
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems. - Tianqi Chen, Weixiang Xu, Weihan Chen, Peisong Wang, Jian Cheng:
Towards Efficient and Accurate Winograd Convolution via Full Quantization. - Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Quantum Bayesian Optimization. - Yudi Zhang, Yali Du, Biwei Huang, Ziyan Wang, Jun Wang, Meng Fang, Mykola Pechenizkiy:
Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach. - Revan MacQueen, James R. Wright:
Guarantees for Self-Play in Multiplayer Games via Polymatrix Decomposability. - Zhanpeng Zeng, Cole Hawkins, Mingyi Hong, Aston Zhang, Nikolaos Pappas, Vikas Singh, Shuai Zheng:
VCC: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens. - Chenghu Du, Junyin Wang, Shuqing Liu, Shengwu Xiong:
Greatness in Simplicity: Unified Self-Cycle Consistency for Parser-Free Virtual Try-On. - Ao Zhang, Hao Fei, Yuan Yao, Wei Ji, Li Li, Zhiyuan Liu, Tat-Seng Chua:
VPGTrans: Transfer Visual Prompt Generator across LLMs. - Stephen Pasteris, Chris Hicks, Vasilios Mavroudis:
Nearest Neighbour with Bandit Feedback. - Tackgeun You, Mijeong Kim, Jungtaek Kim, Bohyung Han:
Generative Neural Fields by Mixtures of Neural Implicit Functions. - Po-Yao Huang, Vasu Sharma, Hu Xu, Chaitanya Ryali, Haoqi Fan, Yanghao Li, Shang-Wen Li, Gargi Ghosh, Jitendra Malik, Christoph Feichtenhofer:
MAViL: Masked Audio-Video Learners. - Zhihan Zhou, Jiangchao Yao, Feng Hong, Ya Zhang, Bo Han, Yanfeng Wang:
Combating Representation Learning Disparity with Geometric Harmonization. - Andrea Nascetti, Ritu Yadav, Kirill Brodt, Qixun Qu, Hongwei Fan, Yuri Shendryk, Isha Shah, Christine Chung:
BioMassters: A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time-series. - Massil Hihat, Stéphane Gaïffas, Guillaume Garrigos, Simon Bussy:
Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization. - Christian Fiedler, Michael Herty, Sebastian Trimpe:
On kernel-based statistical learning theory in the mean field limit. - Mahesh Shakya, Bishesh Khanal:
Benchmarking Encoder-Decoder Architectures for Biplanar X-ray to 3D Bone Shape Reconstruction. - Yining Hong, Haoyu Zhen, Peihao Chen, Shuhong Zheng, Yilun Du, Zhenfang Chen, Chuang Gan:
3D-LLM: Injecting the 3D World into Large Language Models. - Yingtai Xiao, Guanlin He, Danfeng Zhang, Daniel Kifer:
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions. - Chandra Sekhar Mukherjee, Pan Peng, Jiapeng Zhang:
Recovering Unbalanced Communities in the Stochastic Block Model with Application to Clustering with a Faulty Oracle. - Jie Huang, Man Zhou, Jinghao Zhang, Gang Yang, Mingde Yao, Chongyi Li, Zhiwei Xiong, Feng Zhao:
Transition-constant Normalization for Image Enhancement. - Sebastian Ament, Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy:
Unexpected Improvements to Expected Improvement for Bayesian Optimization. - Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan R. Peters:
Pseudo-Likelihood Inference. - Yuxuan Lu, Yuqing Kong:
Calibrating "Cheap Signals" in Peer Review without a Prior. - Yanyu Li, Huan Wang, Qing Jin, Ju Hu, Pavlo Chemerys, Yun Fu, Yanzhi Wang, Sergey Tulyakov, Jian Ren:
SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds. - Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding:
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. - Zhichao Wang, Andrew Engel, Anand D. Sarwate, Ioana Dumitriu, Tony Chiang:
Spectral Evolution and Invariance in Linear-width Neural Networks. - Zhenhailong Wang, Ansel Blume, Sha Li, Genglin Liu, Jaemin Cho, Zineng Tang, Mohit Bansal, Heng Ji:
Paxion: Patching Action Knowledge in Video-Language Foundation Models. - Siwon Kim, Sangdoo Yun, Hwaran Lee, Martin Gubri, Sungroh Yoon, Seong Joon Oh:
ProPILE: Probing Privacy Leakage in Large Language Models. - Moritz Haas, David Holzmüller, Ulrike von Luxburg, Ingo Steinwart:
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension. - Laura Ruis, Akbir Khan, Stella Biderman, Sara Hooker, Tim Rocktäschel, Edward Grefenstette:
The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs. - Xiaohan Lin, Liyuan Li, Boxin Shi, Tiejun Huang, Yuanyuan Mi, Si Wu:
Slow and Weak Attractor Computation Embedded in Fast and Strong E-I Balanced Neural Dynamics. - Juliette Bertrand, Giorgos Kordopatis-Zilos, Yannis Kalantidis, Giorgos Tolias:
Test-time Training for Matching-based Video Object Segmentation. - Abhinav Kumar, Amit Deshpande, Amit Sharma:
Causal Effect Regularization: Automated Detection and Removal of Spurious Correlations. - Hyuna Cho, Minjae Jeong, Sooyeon Jeon, Sungsoo Ahn, Won Hwa Kim:
Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion. - Wenlong Zhang, Xiaohui Li, Guangyuan Shi, Xiangyu Chen, Yu Qiao, Xiaoyun Zhang, Xiao-Ming Wu, Chao Dong:
Real-World Image Super-Resolution as Multi-Task Learning. - Sudhanshu Chanpuriya, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco:
Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings. - Gang Liu, Eric Inae, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang:
Data-Centric Learning from Unlabeled Graphs with Diffusion Model. - Hanna Ziesche, Leonel Rozo:
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies. - Carlos Misael Madrid Padilla, Haotian Xu, Daren Wang, Oscar Hernan Madrid Padilla, Yi Yu:
Change point detection and inference in multivariate non-parametric models under mixing conditions. - Guy Kornowski, Steve Hanneke, Aryeh Kontorovich:
Near-optimal learning with average Hölder smoothness. - Liulei Li, Jianan Wei, Wenguan Wang, Yi Yang:
Neural-Logic Human-Object Interaction Detection. - Suraj Srinivas, Sebastian Bordt, Himabindu Lakkaraju:
Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness. - Kartik Chandra, Tony Chen, Tzu-Mao Li, Jonathan Ragan-Kelley, Josh Tenenbaum:
Inferring the Future by Imagining the Past. - Fraser Mince, Dzung Dinh, Jonas Kgomo, Neil Thompson, Sara Hooker:
The Grand Illusion: The Myth of Software Portability and Implications for ML Progress. - Youzhi Zhang, Bo An, Venkatramanan Siva Subrahmanian:
Computing Optimal Nash Equilibria in Multiplayer Games. - Fangzhou Luo, Xiaolin Wu, Yanhui Guo:
AND: Adversarial Neural Degradation for Learning Blind Image Super-Resolution. - Abeba Birhane, Vinay Uday Prabhu, Sanghyun Han, Vishnu Boddeti, Sasha Luccioni:
Into the LAION's Den: Investigating Hate in Multimodal Datasets. - Haobo Jiang, Mathieu Salzmann, Zheng Dang, Jin Xie, Jian Yang:
SE(3) Diffusion Model-based Point Cloud Registration for Robust 6D Object Pose Estimation. - Lingdong Kong, Shaoyuan Xie, Hanjiang Hu, Lai Xing Ng, Benoit Cottereau, Wei Tsang Ooi:
RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions. - Zhongyi Cai, Ye Shi, Wei Huang, Jingya Wang:
Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning. - Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, LI He, Liang Wang, Bo Zheng, Bo Han:
Combating Bilateral Edge Noise for Robust Link Prediction. - Yuting Hu, Jiajie Li, Florian Klemme, Gi-Joon Nam, Tengfei Ma, Hussam Amrouch, Jinjun Xiong:
SyncTREE: Fast Timing Analysis for Integrated Circuit Design through a Physics-informed Tree-based Graph Neural Network. - Xudong Wang, Shufan Li, Konstantinos Kallidromitis, Yusuke Kato, Kazuki Kozuka, Trevor Darrell:
Hierarchical Open-vocabulary Universal Image Segmentation. - Jinqiu Jin, Haoxuan Li, Fuli Feng, Sihao Ding, Peng Wu, Xiangnan He:
Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach. - Matthew Chang, Aditya Prakash, Saurabh Gupta:
Look Ma, No Hands! Agent-Environment Factorization of Egocentric Videos. - Jing Yu Koh, Daniel Fried, Russ Salakhutdinov:
Generating Images with Multimodal Language Models. - Sizhe Yang, Yanjie Ze, Huazhe Xu:
MoVie: Visual Model-Based Policy Adaptation for View Generalization. - Chen Sun, Calvin Luo, Xingyi Zhou, Anurag Arnab, Cordelia Schmid:
Does Visual Pretraining Help End-to-End Reasoning? - Lingbing Guo, Weiqing Wang, Zhuo Chen, Ningyu Zhang, Zequn Sun, Yixuan Lai, Qiang Zhang, Huajun Chen:
Newton-Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems. - Jiawei Liu, Chunqiu Steven Xia, Yuyao Wang, Lingming Zhang:
Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation. - Kaiyu Yang, Aidan M. Swope, Alex Gu, Rahul Chalamala, Peiyang Song, Shixing Yu, Saad Godil, Ryan J. Prenger, Animashree Anandkumar:
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models. - Talia Konkle, George A. Alvarez:
Cognitive Steering in Deep Neural Networks via Long-Range Modulatory Feedback Connections. - Zenan Li, Yunpeng Huang, Zhaoyu Li, Yuan Yao, Jingwei Xu, Taolue Chen, Xiaoxing Ma, Jian Lu:
Neuro-symbolic Learning Yielding Logical Constraints. - Aaron J. Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Bin Hu:
Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models. - Nathaniel Lahn, Sharath Raghvendra, Kaiyi Zhang:
A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings. - Morteza Ghahremani, Christian Wachinger:
RegBN: Batch Normalization of Multimodal Data with Regularization. - Xinyin Ma, Gongfan Fang, Xinchao Wang:
LLM-Pruner: On the Structural Pruning of Large Language Models. - Yahong Yang, Haizhao Yang, Yang Xiang:
Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives. - Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick:
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. - Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane, Puqian Wang, Nikos Zarifis:
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise. - Ao Sun, Pingchuan Ma, Yuanyuan Yuan, Shuai Wang:
Explain Any Concept: Segment Anything Meets Concept-Based Explanation. - Jiaxing Xu, Yunhan Yang, David Tse Jung Huang, Sophi Shilpa Gururajapathy, Yiping Ke, Miao Qiao, Alan Wang, Haribalan Kumar, Josh McGeown, Eryn Kwon:
Data-Driven Network Neuroscience: On Data Collection and Benchmark. - Eric Neyman, Tim Roughgarden:
No-Regret Learning with Unbounded Losses: The Case of Logarithmic Pooling. - Jialu Li, Mohit Bansal:
PanoGen: Text-Conditioned Panoramic Environment Generation for Vision-and-Language Navigation. - Richard Antonello, Aditya R. Vaidya, Alexander Huth:
Scaling laws for language encoding models in fMRI. - Y. Jennifer Sun, Stephen H. Newman, Elad Hazan:
Optimal Rates for Bandit Nonstochastic Control. - Yuxin Cao, Yian Li, Yumeng Zhu, Derui Wang, Minhui Xue:
Flow-Attention-based Spatio-Temporal Aggregation Network for 3D Mask Detection. - Yi Feng, Hu Fu, Qun Hu, Ping Li, Ioannis Panageas, Bo Peng, Xiao Wang:
On the Last-iterate Convergence in Time-varying Zero-sum Games: Extra Gradient Succeeds where Optimism Fails. - Suhas Shrinivasan, Konstantin-Klemens Lurz, Kelli Restivo, George H. Denfield, Andreas S. Tolias, Edgar Y. Walker, Fabian H. Sinz:
Taking the neural sampling code very seriously: A data-driven approach for evaluating generative models of the visual system. - Alexandru Tifrea, Gizem Yüce, Amartya Sanyal, Fanny Yang:
Can semi-supervised learning use all the data effectively? A lower bound perspective. - Mixue Xie, Shuang Li, Longhui Yuan, Chi Harold Liu, Zehui Dai:
Evolving Standardization for Continual Domain Generalization over Temporal Drift. - Philippe Chatigny, Ivan Sergienko, Ryan Ferguson, Jordan Weir, Maxime Bergeron:
Learning the Efficient Frontier. - Yingcong Li, Kartik Sreenivasan, Angeliki Giannou, Dimitris Papailiopoulos, Samet Oymak:
Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning. - Thao Nguyen, Samir Yitzhak Gadre, Gabriel Ilharco, Sewoong Oh, Ludwig Schmidt:
Improving multimodal datasets with image captioning. - Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard:
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. - Liangliang Shi, Haoyu Zhen, Gu Zhang, Junchi Yan:
Relative Entropic Optimal Transport: a (Prior-aware) Matching Perspective to (Unbalanced) Classification. - Zehan Wang, Yang Zhao, Xize Cheng, Haifeng Huang, Jiageng Liu, Aoxiong Yin, Li Tang, Linjun Li, Yongqi Wang, Ziang Zhang, Zhou Zhao:
Connecting Multi-modal Contrastive Representations. - Heeyoul Kwak, Daeyoung Yun, Yongjune Kim, Sang-Hyo Kim, Jong-Seon No:
Boosting Learning for LDPC Codes to Improve the Error-Floor Performance. - Tianhao Wu, Mingdong Wu, Jiyao Zhang, Yunchong Gan, Hao Dong:
Learning Score-based Grasping Primitive for Human-assisting Dexterous Grasping. - Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang:
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration. - Yun Qu, Boyuan Wang, Jianzhun Shao, Yuhang Jiang, Chen Chen, Zhenbin Ye, Lin Liu, Yang Feng, Lin Lai, Hongyang Qin, Minwen Deng, Juchao Zhuo, Deheng Ye, Qiang Fu, Yang Guang, Wei Yang, Lanxiao Huang, Xiangyang Ji:
Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks. - Simina Brânzei, Mahsa Derakhshan, Negin Golrezaei, Yanjun Han:
Learning and Collusion in Multi-unit Auctions. - Minghua Liu, Chao Xu, Haian Jin, Linghao Chen, Mukund Varma T., Zexiang Xu, Hao Su:
One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization. - Min Wu, Haoze Wu, Clark W. Barrett:
VeriX: Towards Verified Explainability of Deep Neural Networks. - Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Krzysztof Dembczynski:
Generalized test utilities for long-tail performance in extreme multi-label classification. - Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi S. Jaakkola, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Akash Srivastava, Pulkit Agrawal:
Compositional Foundation Models for Hierarchical Planning. - Xin Yan, Hui Fang, Qiang He:
Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks. - Muchao Ye, Ziyi Yin, Tianrong Zhang, Tianyu Du, Jinghui Chen, Ting Wang, Fenglong Ma:
UniT: A Unified Look at Certified Robust Training against Text Adversarial Perturbation. - Rachel A. Ward, Tamara G. Kolda:
Convergence of Alternating Gradient Descent for Matrix Factorization. - Yue Wu, So Yeon Min, Shrimai Prabhumoye, Yonatan Bisk, Russ Salakhutdinov, Amos Azaria, Tom M. Mitchell, Yuanzhi Li:
SPRING: Studying Papers and Reasoning to play Games. - Kalle Kujanpää, Joni Pajarinen, Alexander Ilin:
Hybrid Search for Efficient Planning with Completeness Guarantees. - Jianing Zhu, Yu Geng, Jiangchao Yao, Tongliang Liu, Gang Niu, Masashi Sugiyama, Bo Han:
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation. - Riccardo Giuseppe Margiotta, Sebastian Goldt, Guido Sanguinetti:
Attacks on Online Learners: a Teacher-Student Analysis. - Wenzhi Gao, Qi Deng:
Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization. - Zifan Wang, Saranya Vijayakumar, Kaiji Lu, Vijay Ganesh, Somesh Jha, Matt Fredrikson:
Grounding Neural Inference with Satisfiability Modulo Theories. - Fenggen Yu, Qimin Chen, Maham Tanveer, Ali Mahdavi-Amiri, Hao Zhang:
D2CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts. - Weizhe Lin, Jinghong Chen, Jingbiao Mei, Alexandru Coca, Bill Byrne:
Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question Answering. - Wei Fu, Weihua Du, Jingwei Li, Sunli Chen, Jingzhao Zhang, Yi Wu:
Iteratively Learn Diverse Strategies with State Distance Information. - Fangcheng Zhong, Kyle Fogarty, Param Hanji, Tianhao Wu, Alejandro Sztrajman, Andrew Spielberg, Andrea Tagliasacchi, Petra Bosilj, Cengiz Öztireli:
Neural Fields with Hard Constraints of Arbitrary Differential Order. - Stephen Chung, Ivan Anokhin, David Krueger:
Thinker: Learning to Plan and Act. - David P. Woodruff, Peilin Zhong, Samson Zhou:
Near-Optimal k-Clustering in the Sliding Window Model. - Yuanshao Zhu, Yongchao Ye, Ying Wu, Xiangyu Zhao, James Jian Qiao Yu:
SynMob: Creating High-Fidelity Synthetic GPS Trajectory Dataset for Urban Mobility Analysis. - Guy Bar-Shalom, Yonatan Geifman, Ran El-Yaniv:
Window-Based Distribution Shift Detection for Deep Neural Networks. - Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang:
Towards Label Position Bias in Graph Neural Networks. - Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala:
Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency. - Soroush Ebadian, Aris Filos-Ratsikas, Mohamad Latifian, Nisarg Shah:
Explainable and Efficient Randomized Voting Rules. - Anastasios Angelopoulos, Emmanuel J. Candès, Ryan J. Tibshirani:
Conformal PID Control for Time Series Prediction. - Yujie Lu, Xianjun Yang, Xiujun Li, Xin Eric Wang, William Yang Wang:
LLMScore: Unveiling the Power of Large Language Models in Text-to-Image Synthesis Evaluation. - Wentian Zhang, Haozhe Liu, Bing Li, Jinheng Xie, Yawen Huang, Yuexiang Li, Yefeng Zheng, Bernard Ghanem:
Dynamically Masked Discriminator for GANs. - Bidipta Sarkar, Andy Shih, Dorsa Sadigh:
Diverse Conventions for Human-AI Collaboration. - Rylan Schaeffer, Mikail Khona, Tzuhsuan Ma, Cristóbal Eyzaguirre, Sanmi Koyejo, Ila Fiete:
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells. - Yury Demidovich, Grigory Malinovsky, Igor Sokolov, Peter Richtárik:
A Guide Through the Zoo of Biased SGD. - Simon Schrodi, Danny Stoll, Binxin Ru, Rhea Sukthanker, Thomas Brox, Frank Hutter:
Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars. - Shuai Zhang, Wenqi Jiang:
Data-Informed Geometric Space Selection. - Shivakanth Sujit, Somjit Nath, Pedro H. M. Braga, Samira Ebrahimi Kahou:
Prioritizing Samples in Reinforcement Learning with Reducible Loss. - Alexander Modell, Ian Gallagher, Emma Ceccherini, Nick Whiteley, Patrick Rubin-Delanchy:
Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks. - Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He:
Understanding Contrastive Learning via Distributionally Robust Optimization. - Shuai Li, Yingjie Zhang, Hongtu Zhu, Christina Dan Wang, Hai Shu, Ziqi Chen, Zhuoran Sun, Yanfeng Yang:
K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing. - Kaidi Cao, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi:
Learning Large Graph Property Prediction via Graph Segment Training. - Udaya Ghai, Arushi Gupta, Wenhan Xia, Karan Singh, Elad Hazan:
Online Nonstochastic Model-Free Reinforcement Learning. - Jaeyeon Kim, Asuman E. Ozdaglar, Chanwoo Park, Ernest K. Ryu:
Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value. - Hyun-Jun Choi, Rajan Udwani, Min-hwan Oh:
Cascading Contextual Assortment Bandits. - Zheng Wang, Shikai Fang, Shibo Li, Shandian Zhe:
Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes. - Wojciech Kusa, Óscar E. Mendoza, Matthias Samwald, Petr Knoth, Allan Hanbury:
CSMeD: Bridging the Dataset Gap in Automated Citation Screening for Systematic Literature Reviews. - Che-Ping Tsai, Chih-Kuan Yeh, Pradeep Ravikumar:
Sample based Explanations via Generalized Representers. - Hejie Cui, Xinyu Fang, Zihan Zhang, Ran Xu, Xuan Kan, Xin Liu, Yue Yu, Manling Li, Yangqiu Song, Carl Yang:
Open Visual Knowledge Extraction via Relation-Oriented Multimodality Model Prompting. - Jianqin Luo, Zhexiong Wan, Yuxin Mao, Bo Li, Yuchao Dai:
Continuous Parametric Optical Flow. - Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio:
Reusable Slotwise Mechanisms. - Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal:
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning. - Beichen Zhang, Kun Zhou, Xilin Wei, Xin Zhao, Jing Sha, Shijin Wang, Ji-Rong Wen:
Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning. - Mingtian Zhang, Alex Hawkins-Hooker, Brooks Paige, David Barber:
Moment Matching Denoising Gibbs Sampling. - Arthur Jacot:
Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff. - Ruitu Xu, Yifei Min, Tianhao Wang:
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits. - Antônio H. Ribeiro, Dave Zachariah, Francis Bach, Thomas B. Schön:
Regularization properties of adversarially-trained linear regression. - Florian Felten, Lucas N. Alegre, Ann Nowé, Ana L. C. Bazzan, El-Ghazali Talbi, Grégoire Danoy, Bruno C. da Silva:
A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning. - Shihang Feng, Hanchen Wang, Chengyuan Deng, Yinan Feng, Yanhua Liu, Min Zhu, Peng Jin, Yinpeng Chen, Youzuo Lin:
EFWI: Multiparameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties. - Jin-Hui Wu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou:
Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent. - Dmitry Chistikov, Matthias Englert, Ranko Lazic:
Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs. - Junwoo Cho, Seungtae Nam, Hyunmo Yang, Seok-Bae Yun, Youngjoon Hong, Eunbyung Park:
Separable Physics-Informed Neural Networks. - Qingyao Sun, Kevin P. Murphy, Sayna Ebrahimi, Alexander D'Amour:
Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations. - Bill Yuchen Lin, Yicheng Fu, Karina Yang, Faeze Brahman, Shiyu Huang, Chandra Bhagavatula, Prithviraj Ammanabrolu, Yejin Choi, Xiang Ren:
SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks. - John Yang, Akshara Prabhakar, Karthik Narasimhan, Shunyu Yao:
InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback. - Matthew Fisher, Chris J. Oates:
Gradient-Free Kernel Stein Discrepancy. - Lunhao Duan, Shanshan Zhao, Nan Xue, Mingming Gong, Gui-Song Xia, Dacheng Tao:
ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding. - Michael Scherbela, Leon Gerard, Philipp Grohs:
Variational Monte Carlo on a Budget - Fine-tuning pre-trained Neural Wavefunctions. - Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine:
ReDS: Offline RL With Heteroskedastic Datasets via Support Constraints. - Yiyou Sun, Zhenmei Shi, Yixuan Li:
A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning. - Amir Zandieh, Insu Han, Haim Avron:
Near Optimal Reconstruction of Spherical Harmonic Expansions. - Qian Huang, Eric Zelikman, Sarah Chen, Yuhuai Wu, Gregory Valiant, Percy Liang:
Lexinvariant Language Models. - Suman Bhoi, Mong-Li Lee, Wynne Hsu, Ngiap Chuan Tan:
REFINE: A Fine-Grained Medication Recommendation System Using Deep Learning and Personalized Drug Interaction Modeling. - Farzad Pourkamali, Nicolas Macris:
Bayesian Extensive-Rank Matrix Factorization with Rotational Invariant Priors. - Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung:
Optimal Transport Model Distributional Robustness. - Wenxuan Ma, Shuang Li, Lincan Cai, Jingxuan Kang:
Language Semantic Graph Guided Data-Efficient Learning. - Thomas E. Yerxa, Yilun Kuang, Eero P. Simoncelli, SueYeon Chung:
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations. - Yong-Hyun Park, Mingi Kwon, Jaewoong Choi, Junghyo Jo, Youngjung Uh:
Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry. - Hanwen Jiang, Santhosh Kumar Ramakrishnan, Kristen Grauman:
Single-Stage Visual Query Localization in Egocentric Videos. - Pai Chet Ng, Zhixiang Chi, Yannick Verdie, Juwei Lu, Konstantinos N. Plataniotis:
Hyper-Skin: A Hyperspectral Dataset for Reconstructing Facial Skin-Spectra from RGB Images. - Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama:
Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems. - Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy Nguyen:
Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise. - Kyowoon Lee, Seongun Kim, Jaesik Choi:
Refining Diffusion Planner for Reliable Behavior Synthesis by Automatic Detection of Infeasible Plans. - Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan, Xiangnan He:
Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion. - Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop:
Conditional score-based diffusion models for Bayesian inference in infinite dimensions. - Emmanuel Abbe, Elisabetta Cornacchia, Aryo Lotfi:
Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs. - Matthew B. A. McDermott, Bret Nestor, Peniel N. Argaw, Isaac S. Kohane:
Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events. - Zitang Sun, Yen-Ju Chen, Yung-Hao Yang, Shin'ya Nishida:
Modeling Human Visual Motion Processing with Trainable Motion Energy Sensing and a Self-attention Network. - Arjun Somayazulu, Changan Chen, Kristen Grauman:
Self-Supervised Visual Acoustic Matching. - Ayoub El Hanchi, Murat A. Erdogdu:
Optimal Excess Risk Bounds for Empirical Risk Minimization on p-Norm Linear Regression. - Shogo Iwazaki, Shion Takeno, Tomohiko Tanabe, Mitsuru Irie:
Failure-Aware Gaussian Process Optimization with Regret Bounds. - Guanlin Liu, Lifeng Lai:
Efficient Adversarial Attacks on Online Multi-agent Reinforcement Learning. - Caspar Oesterheld, Johannes Treutlein, Roger B. Grosse, Vincent Conitzer, Jakob N. Foerster:
Similarity-based cooperative equilibrium. - Shentao Yang, Shujian Zhang, Congying Xia, Yihao Feng, Caiming Xiong, Mingyuan Zhou:
Preference-grounded Token-level Guidance for Language Model Fine-tuning. - Lei Xu, Lei Chen, Rong Wang, Feiping Nie, Xuelong Li:
Joint Feature and Differentiable k-NN Graph Learning using Dirichlet Energy. - Emmanuel Abbe, Samy Bengio, Enric Boix-Adserà, Etai Littwin, Joshua M. Susskind:
Transformers learn through gradual rank increase. - Jong Wook Bae, Jungho Kim, Junyong Yun, Changwon Kang, Jeongseon Choi, Chanhyeok Kim, Junho Lee, Jungwook Choi, Jun Won Choi:
SiT Dataset: Socially Interactive Pedestrian Trajectory Dataset for Social Navigation Robots. - Hao Li, Jingkuan Song, Lianli Gao, Xiaosu Zhu, Hengtao Shen:
Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval. - Emile van Krieken, Thiviyan Thanapalasingam, Jakub M. Tomczak, Frank van Harmelen, Annette ten Teije:
A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference. - Yajie Bao, Amarda Shehu, Mingrui Liu:
Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization. - Tianyu Liu, Yuge Wang, Rex Ying, Hongyu Zhao:
MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data. - Jiaming Ji, Mickel Liu, Josef Dai, Xuehai Pan, Chi Zhang, Ce Bian, Boyuan Chen, Ruiyang Sun, Yizhou Wang, Yaodong Yang:
BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset. - Paul S. Scotti, Atmadeep Banerjee, Jimmie Goode, Stepan Shabalin, Alex Nguyen, Ethan Cohen, Aidan J. Dempster, Nathalie Verlinde, Elad Yundler, David Weisberg, Kenneth A. Norman, Tanishq Mathew Abraham:
Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priors. - Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim:
Exploring Why Object Recognition Performance Degrades Across Income Levels and Geographies with Factor Annotations. - Alon Albalak, Colin A. Raffel, William Yang Wang:
Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data. - Lemin Kong, Jiajin Li, Jianheng Tang, Anthony Man-Cho So:
Outlier-Robust Gromov-Wasserstein for Graph Data. - Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M.-C. Höhne:
Labeling Neural Representations with Inverse Recognition. - Yang Qin, Yuan Sun, Dezhong Peng, Joey Tianyi Zhou, Xi Peng, Peng Hu:
Cross-modal Active Complementary Learning with Self-refining Correspondence. - Zijiao Chen, Jiaxin Qing, Juan Helen Zhou:
Cinematic Mindscapes: High-quality Video Reconstruction from Brain Activity. - Yufei Cui, Ziquan Liu, Yixin Chen, Yuchen Lu, Xinyue Yu, Xue (Steve) Liu, Tei-Wei Kuo, Miguel Rodrigues, Chun Jason Xue, Antoni B. Chan:
Retrieval-Augmented Multiple Instance Learning. - Yijian Qin, Xin Wang, Ziwei Zhang, Hong Chen, Wenwu Zhu:
Multi-task Graph Neural Architecture Search with Task-aware Collaboration and Curriculum. - Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Payel Das, Siva Reddy:
The Impact of Positional Encoding on Length Generalization in Transformers. - Ryan Singh, Christopher L. Buckley:
Attention as Implicit Structural Inference. - Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka:
Nearly Tight Bounds For Differentially Private Multiway Cut. - Allan Zhou, Kaien Yang, Kaylee Burns, Adriano Cardace, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn:
Permutation Equivariant Neural Functionals. - Lingfeng Yang, Yueze Wang, Xiang Li, Xinlong Wang, Jian Yang:
Fine-Grained Visual Prompting. - Shiyu Hu, Dailing Zhang, Meiqi Wu, Xiaokun Feng, Xuchen Li, Xin Zhao, Kaiqi Huang:
A Multi-modal Global Instance Tracking Benchmark (MGIT): Better Locating Target in Complex Spatio-temporal and Causal Relationship. - Yixuan Zhang, Quyu Kong, Feng Zhou:
Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes. - Alex Fang, Simon Kornblith, Ludwig Schmidt:
Does progress on ImageNet transfer to real-world datasets? - Yao Mu, Qinglong Zhang, Mengkang Hu, Wenhai Wang, Mingyu Ding, Jun Jin, Bin Wang, Jifeng Dai, Yu Qiao, Ping Luo:
EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought. - Marcello Massimo Negri, Fabricio Arend Torres, Volker Roth:
Conditional Matrix Flows for Gaussian Graphical Models. - Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien:
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. - Dingkang Yang, Kun Yang, Yuzheng Wang, Jing Liu, Zhi Xu, Rongbin Yin, Peng Zhai, Lihua Zhang:
How2comm: Communication-Efficient and Collaboration-Pragmatic Multi-Agent Perception. - Viraj Prabhu, Sriram Yenamandra, Prithvijit Chattopadhyay, Judy Hoffman:
LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images. - Christos Boutsikas, Petros Drineas, Marios Mertzanidis, Alexandros Psomas, Paritosh Verma:
Refined Mechanism Design for Approximately Structured Priors via Active Regression. - Amit Daniely, Nati Srebro, Gal Vardi:
Most Neural Networks Are Almost Learnable. - Tianyuan Teng, Kevin Li, Hang Zhang:
Bounded rationality in structured density estimation. - Zhuoman Liu, Bo Yang, Yan Luximon, Ajay Kumar, Jinxi Li:
RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency. - Jing Lin, Ailing Zeng, Shunlin Lu, Yuanhao Cai, Ruimao Zhang, Haoqian Wang, Lei Zhang:
Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Dataset. - Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain:
Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints. - Dimitris Christou, Stratis Skoulakis, Volkan Cevher:
Efficient Online Clustering with Moving Costs. - Manuel Brack, Felix Friedrich, Dominik Hintersdorf, Lukas Struppek, Patrick Schramowski, Kristian Kersting:
SEGA: Instructing Text-to-Image Models using Semantic Guidance. - Peng Cui, Dan Zhang, Zhijie Deng, Yinpeng Dong, Jun Zhu:
Learning Sample Difficulty from Pre-trained Models for Reliable Prediction. - Yoav Kolumbus, Menahem Levy, Noam Nisan:
Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling. - Zeyu Lu, Di Huang, Lei Bai, Jingjing Qu, Chengyue Wu, Xihui Liu, Wanli Ouyang:
Seeing is not always believing: Benchmarking Human and Model Perception of AI-Generated Images. - Pengxiang Wu, Siman Wang, Kevin Dela Rosa, Derek Hao Hu:
FORB: A Flat Object Retrieval Benchmark for Universal Image Embedding. - Qi Qian, Yuanhong Xu, Juhua Hu:
Intra-Modal Proxy Learning for Zero-Shot Visual Categorization with CLIP. - Yilin Lyu, Liyuan Wang, Xingxing Zhang, Zicheng Sun, Hang Su, Jun Zhu, Liping Jing:
Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation. - Elia Turner, Omri Barak:
The Simplicity Bias in Multi-Task RNNs: Shared Attractors, Reuse of Dynamics, and Geometric Representation. - Leah Chrestien, Stefan Edelkamp, Antonín Komenda, Tomás Pevný:
Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal. - Zilai Zeng, Ce Zhang, Shijie Wang, Chen Sun:
Goal-Conditioned Predictive Coding for Offline Reinforcement Learning. - Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang:
Exposing Attention Glitches with Flip-Flop Language Modeling. - Yue Lin, Wenhao Li, Hongyuan Zha, Baoxiang Wang:
Information Design in Multi-Agent Reinforcement Learning. - Hanzhong Guo, Cheng Lu, Fan Bao, Tianyu Pang, Shuicheng Yan, Chao Du, Chongxuan Li:
Gaussian Mixture Solvers for Diffusion Models. - Yifan Zhang, Haowei He, Zhiquan Tan, Yang Yuan:
Trade-off Between Efficiency and Consistency for Removal-based Explanations. - Di Luo, Jiayu Shen, Rumen Dangovski, Marin Soljacic:
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning. - Semih Cayci, Atilla Eryilmaz:
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards. - Yubin Shi, Yixuan Chen, Mingzhi Dong, Xiaochen Yang, Dongsheng Li, Yujiang Wang, Robert P. Dick, Qin Lv, Yingying Zhao, Fan Yang, Tun Lu, Ning Gu, Li Shang:
Train Faster, Perform Better: Modular Adaptive Training in Over-Parameterized Models. - Ming-Kun Xie, Jiahao Xiao, Hao-Zhe Liu, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang:
Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning. - Kobbi Nissim, Uri Stemmer, Eliad Tsfadia:
Adaptive Data Analysis in a Balanced Adversarial Model. - Filip Ekström Kelvinius, Dimitar Georgiev, Artur P. Toshev, Johannes Gasteiger:
Accelerating Molecular Graph Neural Networks via Knowledge Distillation. - Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt J. Kusner:
No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models. - Muhammed Fatih Balin, Ümit V. Çatalyürek:
Layer-Neighbor Sampling - Defusing Neighborhood Explosion in GNNs. - Zerui Tao, Toshihisa Tanaka, Qibin Zhao:
Undirected Probabilistic Model for Tensor Decomposition. - Zhiyuan Liu, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua:
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules. - Shaokui Wei, Mingda Zhang, Hongyuan Zha, Baoyuan Wu:
Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples. - Charlie Marx, Sofian Zalouk, Stefano Ermon:
Calibration by Distribution Matching: Trainable Kernel Calibration Metrics. - Arthur C. W. da Cunha, Francesco D'Amore, Emanuele Natale:
Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets. - Amine Ouasfi, Adnane Boukhayma:
Robustifying Generalizable Implicit Shape Networks with a Tunable Non-Parametric Model. - Jiazhong Cen, Zanwei Zhou, Jiemin Fang, Chen Yang, Wei Shen, Lingxi Xie, Dongsheng Jiang, Xiaopeng Zhang, Qi Tian:
Segment Anything in 3D with NeRFs. - Hanhan Zhou, Tian Lan, Guru Venkataramani, Wenbo Ding:
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction. - Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro:
Small batch deep reinforcement learning. - Zijie Geng, Xijun Li, Jie Wang, Xiao Li, Yongdong Zhang, Feng Wu:
A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability. - Maurice Weber, Carlo Siebenschuh, Rory Butler, Anton Alexandrov, Valdemar Thanner, Georgios Tsolakis, Haris Jabbar, Ian T. Foster, Bo Li, Rick Stevens, Ce Zhang:
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data. - Lorenzo Beretta, Vincent Cohen-Addad, Silvio Lattanzi, Nikos Parotsidis:
Multi-Swap k-Means++. - Kansei Ushiyama, Shun Sato, Takayasu Matsuo:
A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization. - Nina Montaña Brown, Shaheer U. Saeed, Ahmed Abdulaal, Thomas Dowrick, Yakup Kilic, Sophie Wilkinson, Jack Gao, Meghavi Mashar, Chloe He, Alkisti Stavropoulou, Emma Thomson, Zachary M. C. Baum, Simone Foti, Brian R. Davidson, Yipeng Hu, Matthew J. Clarkson:
SARAMIS: Simulation Assets for Robotic Assisted and Minimally Invasive Surgery. - Hanzhuo Huang, Yufan Feng, Cheng Shi, Lan Xu, Jingyi Yu, Sibei Yang:
Free-Bloom: Zero-Shot Text-to-Video Generator with LLM Director and LDM Animator. - Mikaela Angelina Uy, Kiyohiro Nakayama, Guandao Yang, Rahul Krishna Thomas, Leonidas J. Guibas, Ke Li:
NeRF Revisited: Fixing Quadrature Instability in Volume Rendering. - Dongkuk Si, Chulhee Yun:
Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima. - Raunak Kumar, Sarah Dean, Robert Kleinberg:
Online Convex Optimization with Unbounded Memory. - Sang Keun Choe, Sanket Vaibhav Mehta, Hwijeen Ahn, Willie Neiswanger, Pengtao Xie, Emma Strubell, Eric P. Xing:
Making Scalable Meta Learning Practical. - Kai Wang, Fei Yang, Shiqi Yang, Muhammad Atif Butt, Joost van de Weijer:
Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing. - Daoze Zhang, Zhizhang Yuan, Yang Yang, Junru Chen, Jingjing Wang, Yafeng Li:
Brant: Foundation Model for Intracranial Neural Signal. - Xingjian Bai, Guangyi He, Yifan Jiang, Jan Oblój:
Wasserstein distributional robustness of neural networks. - Camilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec:
High dimensional, tabular deep learning with an auxiliary knowledge graph. - Valerii Iakovlev, Markus Heinonen, Harri Lähdesmäki:
Learning Space-Time Continuous Latent Neural PDEs from Partially Observed States. - Xiaowen Jiang, Sebastian U. Stich:
Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction. - Zhuoyan Luo, Yicheng Xiao, Yong Liu, Shuyan Li, Yitong Wang, Yansong Tang, Xiu Li, Yujiu Yang:
SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation. - Abhishek Singh, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar:
Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release. - Han Shao, Avrim Blum, Omar Montasser:
Strategic Classification under Unknown Personalized Manipulation. - Vadim Tschernezki, Ahmad Darkhalil, Zhifan Zhu, David Fouhey, Iro Laina, Diane Larlus, Dima Damen, Andrea Vedaldi:
EPIC Fields: Marrying 3D Geometry and Video Understanding. - Noam Razin, Tom Verbin, Nadav Cohen:
On the Ability of Graph Neural Networks to Model Interactions Between Vertices. - Kunxun Qi, Jianfeng Du, Hai Wan:
Learning from Both Structural and Textual Knowledge for Inductive Knowledge Graph Completion. - Xingjian Bai, Christian Coester:
Sorting with Predictions. - Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang:
Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. - Peiran Dong, Song Guo, Junxiao Wang, Bingjie Wang, Jiewei Zhang, Ziming Liu:
Towards Test-Time Refusals via Concept Negation. - Zhenfei Yin, Jiong Wang, Jianjian Cao, Zhelun Shi, Dingning Liu, Mukai Li, Xiaoshui Huang, Zhiyong Wang, Lu Sheng, Lei Bai, Jing Shao, Wanli Ouyang:
LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark. - Nicolas Emmenegger, Mojmir Mutny, Andreas Krause:
Likelihood Ratio Confidence Sets for Sequential Decision Making. - Kexin Huang, Ying Jin, Emmanuel J. Candès, Jure Leskovec:
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks. - Dragos-Georgian Corlatescu, Alexandru Dinu, Mihaela Gaman, Paul Sumedrea:
EMBERSim: A Large-Scale Databank for Boosting Similarity Search in Malware Analysis. - Zekun Qi, Muzhou Yu, Runpei Dong, Kaisheng Ma:
VPP: Efficient Conditional 3D Generation via Voxel-Point Progressive Representation. - Vaisakh Shaj, Saleh Gholam Zadeh, Ozan Demir, Luiz R. Douat, Gerhard Neumann:
Multi Time Scale World Models. - Vivien Cabannes, Stefano Vigogna:
How many samples are needed to leverage smoothness? - Fateme Jamshidi, Sina Akbari, Negar Kiyavash:
Causal Imitability Under Context-Specific Independence Relations. - Jiaxin Shi, Lester Mackey:
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent. - Jacob Lindbäck, Zesen Wang, Mikael Johansson:
Bringing regularized optimal transport to lightspeed: a splitting method adapted for GPUs. - Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller:
Use perturbations when learning from explanations. - Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, Ludwig Schmidt:
VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models. - Peter Nickl, Lu Xu, Dharmesh Tailor, Thomas Möllenhoff, Mohammad Emtiyaz Khan:
The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data. - Haoting Zhang, Jinghai He, Rhonda Righter, Zuo-Jun Max Shen, Zeyu Zheng:
Contextual Gaussian Process Bandits with Neural Networks. - Ivaxi Sheth, Samira Ebrahimi Kahou:
Auxiliary Losses for Learning Generalizable Concept-based Models. - Zhongqi Yue, Qianru Sun, Hanwang Zhang:
Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation. - Caroline Lee, Jane Han, Feilong Ma, Jiahui Guo, James V. Haxby, Christopher Baldassano:
Hyper-HMM: aligning human brains and semantic features in a common latent event space. - Sehyun Hwang, Sohyun Lee, Hoyoung Kim, Minhyeon Oh, Jungseul Ok, Suha Kwak:
Active Learning for Semantic Segmentation with Multi-class Label Query. - Hao Wang, Luxi He, Rui Gao, Flávio P. Calmon:
Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions. - Konstantinos P. Panousis, Sotirios Chatzis:
DISCOVER: Making Vision Networks Interpretable via Competition and Dissection. - Erik Arakelyan, Pasquale Minervini, Daniel Daza, Michael Cochez, Isabelle Augenstein:
Adapting Neural Link Predictors for Data-Efficient Complex Query Answering. - Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander J. Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. - Kai Klede, Thomas Altstidl, Dario Zanca, Bjoern M. Eskofier:
p-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison. - Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon:
On Computing Pairwise Statistics with Local Differential Privacy. - Weipu Zhang, Gang Wang, Jian Sun, Yetian Yuan, Gao Huang:
STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning. - Yue Tan, Chen Chen, Weiming Zhuang, Xin Dong, Lingjuan Lyu, Guodong Long:
Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning. - Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness:
Self-Predictive Universal AI. - Hyojun Go, JinYoung Kim, Yunsung Lee, Seunghyun Lee, Shinhyeok Oh, Hyeongdon Moon, Seungtaek Choi:
Addressing Negative Transfer in Diffusion Models. - Ziqian Zhong, Ziming Liu, Max Tegmark, Jacob Andreas:
The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks. - Samuel Hurault, Ulugbek Kamilov, Arthur Leclaire, Nicolas Papadakis:
Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems. - Ilias Diakonikolas, Daniel Kane, Yuxin Sun:
SQ Lower Bounds for Learning Mixtures of Linear Classifiers. - Kyriakos Flouris, Ender Konukoglu:
Canonical normalizing flows for manifold learning. - Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima:
Regularizing Neural Networks with Meta-Learning Generative Models. - Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian:
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information. - Paul Pu Liang, Yun Cheng, Xiang Fan, Chun Kai Ling, Suzanne Nie, Richard J. Chen, Zihao Deng, Nicholas B. Allen, Randy Auerbach, Faisal Mahmood, Russ Salakhutdinov, Louis-Philippe Morency:
Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework. - Qitao Zhao, Ce Zheng, Mengyuan Liu, Chen Chen:
A Single 2D Pose with Context is Worth Hundreds for 3D Human Pose Estimation. - Qi Chen, Changjian Shui, Ligong Han, Mario Marchand:
On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm. - Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, Mohit Iyyer:
Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense. - Xiaoxuan Ma, Stephan P. Kaufhold, Jiajun Su, Wentao Zhu, Jack Terwilliger, Andres Meza, Yixin Zhu, Federico Rossano, Yizhou Wang:
ChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors. - Benjamin Hoover, Yuchen Liang, Bao Pham, Rameswar Panda, Hendrik Strobelt, Duen Horng Chau, Mohammed J. Zaki, Dmitry Krotov:
Energy Transformer. - Andrea Schioppa, Katja Filippova, Ivan Titov, Polina Zablotskaia:
Theoretical and Practical Perspectives on what Influence Functions Do. - Boris Ivanovic, Guanyu Song, Igor Gilitschenski, Marco Pavone:
trajdata: A Unified Interface to Multiple Human Trajectory Datasets. - Jerry Yao-Chieh Hu, Donglin Yang, Dennis Wu, Chenwei Xu, Bo-Yu Chen, Han Liu:
On Sparse Modern Hopfield Model. - Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar:
D-CIPHER: Discovery of Closed-form Partial Differential Equations. - Ruoxi Jiang, Peter Y. Lu, Elena Orlova, Rebecca Willett:
Training neural operators to preserve invariant measures of chaotic attractors. - Matthew Wicker, Vihari Piratla, Adrian Weller:
Certification of Distributional Individual Fairness. - Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello:
Leveraging sparse and shared feature activations for disentangled representation learning. - Simon Frieder, Luca Pinchetti, Alexis Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Petersen, Julius Berner:
Mathematical Capabilities of ChatGPT. - Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed:
A Unified Framework for U-Net Design and Analysis. - Renchunzi Xie, Hongxin Wei, Lei Feng, Yuzhou Cao, Bo An:
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error. - Aaditya K. Singh, Stephanie C. Y. Chan, Ted Moskovitz, Erin Grant, Andrew M. Saxe, Felix Hill:
The Transient Nature of Emergent In-Context Learning in Transformers. - Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari, Nati Srebro:
When is Agnostic Reinforcement Learning Statistically Tractable? - Yeongbin Kim, Gautam Singh, Junyeong Park, Çaglar Gülçehre, Sungjin Ahn:
Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models. - Yun-Yun Tsai, Chengzhi Mao, Junfeng Yang:
Convolutional Visual Prompt for Robust Visual Perception. - Duy M. H. Nguyen, Hoang Nguyen, Nghiem Tuong Diep, Tan Ngoc Pham, Tri Cao, Binh T. Nguyen, Paul Swoboda, Nhat Ho, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag, Mathias Niepert:
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching. - Jiarui Jin, Xianyu Chen, Fanghua Ye, Mengyue Yang, Yue Feng, Weinan Zhang, Yong Yu, Jun Wang:
Lending Interaction Wings to Recommender Systems with Conversational Agents. - Rithesh Kumar, Prem Seetharaman, Alejandro Luebs, Ishaan Kumar, Kundan Kumar:
High-Fidelity Audio Compression with Improved RVQGAN. - Leonidas Tsepenekas, Ivan Brugere, Freddy Lécué, Daniele Magazzeni:
Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions. - Zijie Li, Dule Shu, Amir Barati Farimani:
Scalable Transformer for PDE Surrogate Modeling. - Khashayar Gatmiry, Zhiyuan Li, Tengyu Ma, Sashank J. Reddi, Stefanie Jegelka, Ching-Yao Chuang:
What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models. - Shutong Ding, Tianyu Cui, Jingya Wang, Ye Shi:
Two Sides of The Same Coin: Bridging Deep Equilibrium Models and Neural ODEs via Homotopy Continuation. - Stella Biderman, USVSN Sai Prashanth, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony, Shivanshu Purohit, Edward Raff:
Emergent and Predictable Memorization in Large Language Models. - Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Samual Stevens, Boshi Wang, Huan Sun, Yu Su:
Mind2Web: Towards a Generalist Agent for the Web. - Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser, Mary-Anne Hartley:
MultiMoDN - Multimodal, Multi-Task, Interpretable Modular Networks. - Shengyuan Chen, Yunfeng Cai, Huang Fang, Xiao Huang, Mingming Sun:
Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs. - Abraham D. Smith, Michael J. Catanzaro, Gabrielle Angeloro, Nirav Patel, Paul Bendich:
Topological Parallax: A Geometric Specification for Deep Perception Models. - Zhicheng Sun, Yadong Mu:
Rewiring Neurons in Non-Stationary Environments. - Wenhao Wang, Yifan Sun, Wei Li, Yi Yang:
TransHP: Image Classification with Hierarchical Prompting. - Antti Koskela, Tejas D. Kulkarni:
Practical Differentially Private Hyperparameter Tuning with Subsampling. - Hyunseung Kim, Byungkun Lee, Hojoon Lee, Dongyoon Hwang, Sejik Park, Kyushik Min, Jaegul Choo:
Learning to Discover Skills through Guidance. - Gabriele Farina, Charilaos Pipis:
Polynomial-Time Linear-Swap Regret Minimization in Imperfect-Information Sequential Games. - Yo Joong Choe, Aditya Gangrade, Aaditya Ramdas:
Counterfactually Comparing Abstaining Classifiers. - Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong:
Video Timeline Modeling For News Story Understanding. - Hongyu Zang, Xin Li, Leiji Zhang, Yang Liu, Baigui Sun, Riashat Islam, Remi Tachet des Combes, Romain Laroche:
Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning. - Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang:
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting. - Tycho F. A. van der Ouderaa, Alexander Immer, Mark van der Wilk:
Learning Layer-wise Equivariances Automatically using Gradients. - Mingjia Shi, Yuhao Zhou, Kai Wang, Huaizheng Zhang, Shudong Huang, Qing Ye, Jiancheng Lv:
PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning. - Nazarii Tupitsa, Abdulla Jasem Almansoori, Yanlin Wu, Martin Takác, Karthik Nandakumar, Samuel Horváth, Eduard Gorbunov:
Byzantine-Tolerant Methods for Distributed Variational Inequalities. - Sizhe Wei, Yuxi Wei, Yue Hu, Yifan Lu, Yiqi Zhong, Siheng Chen, Ya Zhang:
Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow. - Tzu-Heng Huang, Harit Vishwakarma, Frederic Sala:
Train 'n Trade: Foundations of Parameter Markets. - Mehdi Azabou, Michael Mendelson, Nauman Ahad, Maks Sorokin, Shantanu Thakoor, Carolina Urzay, Eva L. Dyer:
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis. - Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet:
A Measure-Theoretic Axiomatisation of Causality. - Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, Jianfeng Gao:
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day. - Jinjin Gu, Xianzheng Ma, Xiangtao Kong, Yu Qiao, Chao Dong:
Networks are Slacking Off: Understanding Generalization Problem in Image Deraining. - Xiaojun Guo, Yifei Wang, Zeming Wei, Yisen Wang:
Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning. - Zijian Zhou, Oluwatosin Alabi, Meng Wei, Tom Vercauteren, Miaojing Shi:
Text Promptable Surgical Instrument Segmentation with Vision-Language Models. - Kevin Fu Jiang, Weixin Liang, James Y. Zou, Yongchan Kwon:
OpenDataVal: a Unified Benchmark for Data Valuation. - Arghya Datta, Sayak Chakrabarty:
On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis. - Aleksandr Beznosikov, Martin Takác, Alexander V. Gasnikov:
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities. - Jiangtao Zhang, Shunyu Liu, Jie Song, Tongtian Zhu, Zhengqi Xu, Mingli Song:
Lookaround Optimizer: k steps around, 1 step average. - Eric J. Michaud, Ziming Liu, Uzay Girit, Max Tegmark:
The Quantization Model of Neural Scaling. - Simone Fioravanti, Michele Flammini, Bojana Kodric, Giovanna Varricchio:
ε-fractional core stability in Hedonic Games. - Lei Zhang, Ji-Fu Li, Wei Wang:
Semi-Supervised Domain Generalization with Known and Unknown Classes. - Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup:
When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability. - Elan Rosenfeld, Saurabh Garg:
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy. - Sivaramakrishnan Swaminathan, Antoine Dedieu, Rajkumar Vasudeva Raju, Murray Shanahan, Miguel Lázaro-Gredilla, Dileep George:
Schema-learning and rebinding as mechanisms of in-context learning and emergence. - Denis Kuznedelev, Eldar Kurtic, Elias Frantar, Dan Alistarh:
CAP: Correlation-Aware Pruning for Highly-Accurate Sparse Vision Models. - Yonatan Dukler, Alessandro Achille, Hao Yang, Varsha Vivek, Luca Zancato, Benjamin Bowman, Avinash Ravichandran, Charless C. Fowlkes, Ashwin Swaminathan, Stefano Soatto:
Your representations are in the network: composable and parallel adaptation for large scale models. - Jiali Cui, Tian Han:
Learning Energy-based Model via Dual-MCMC Teaching. - Drew Linsley, Ivan F. Rodriguez Rodriguez, Thomas Fel, Michael Arcaro, Saloni Sharma, Margaret S. Livingstone, Thomas Serre:
Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex. - Jingfeng Wu, Wennan Zhu, Peter Kairouz, Vladimir Braverman:
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance. - Federico Errica:
On Class Distributions Induced by Nearest Neighbor Graphs for Node Classification of Tabular Data. - Mingyu Xu, Zheng Lian, Bin Liu, Jianhua Tao:
VRA: Variational Rectified Activation for Out-of-distribution Detection. - Thibault Randrianarisoa, Botond Szabó:
Variational Gaussian processes for linear inverse problems. - Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak T. Kiani:
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. - Jialin Chen, Rex Ying:
TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery. - David Uthus, Garrett Tanzer, Manfred Georg:
YouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus. - Guojun Xiong, Jian Li:
Finite-Time Analysis of Whittle Index based Q-Learning for Restless Multi-Armed Bandits with Neural Network Function Approximation. - Yu-Jie Zhang, Zhen-Yu Zhang, Peng Zhao, Masashi Sugiyama:
Adapting to Continuous Covariate Shift via Online Density Ratio Estimation. - Zheng Chen, Yulun Zhang, Ding Liu, Bin Xia, Jinjin Gu, Linghe Kong, Xin Yuan:
Hierarchical Integration Diffusion Model for Realistic Image Deblurring. - Jishnu Ray Chowdhury, Cornelia Caragea:
Efficient Beam Tree Recursion. - Cheng-Hao Tu, Hong-You Chen, Zheda Mai, Jike Zhong, Vardaan Pahuja, Tanya Y. Berger-Wolf, Song Gao, Charles V. Stewart, Yu Su, Wei-Lun Chao:
Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data. - Divin Yan, Gengchen Wei, Chen Yang, Shengzhong Zhang, Zengfeng Huang:
Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition. - Daolang Huang, Manuel Haussmann, Ulpu Remes, St John, Grégoire Clarté, Kevin Sebastian Luck, Samuel Kaski, Luigi Acerbi:
Practical Equivariances via Relational Conditional Neural Processes. - Jihyun Lee, Junbong Jang, Donghwan Kim, Minhyuk Sung, Tae-Kyun Kim:
FourierHandFlow: Neural 4D Hand Representation Using Fourier Query Flow. - Akifumi Wachi, Wataru Hashimoto, Xun Shen, Kazumune Hashimoto:
Safe Exploration in Reinforcement Learning: A Generalized Formulation and Algorithms. - Qi Han, Yuxuan Cai, Xiangyu Zhang:
RevColV2: Exploring Disentangled Representations in Masked Image Modeling. - Shengbang Tong, Erik Jones, Jacob Steinhardt:
Mass-Producing Failures of Multimodal Systems with Language Models. - Sujin Jang, Dae Ung Jo, Sung Ju Hwang, Dongwook Lee, Daehyun Ji:
STXD: Structural and Temporal Cross-Modal Distillation for Multi-View 3D Object Detection. - Micah Goldblum, Hossein Souri, Renkun Ni, Manli Shu, Viraj Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Mark Ibrahim, Adrien Bardes, Judy Hoffman, Rama Chellappa, Andrew Gordon Wilson, Tom Goldstein:
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks. - Florian Seligmann, Philipp Becker, Michael Volpp, Gerhard Neumann:
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift. - Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion:
(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability. - Michalis K. Titsias:
Optimal Preconditioning and Fisher Adaptive Langevin Sampling. - Yang Yu, Qi Liu, Kai Zhang, Yuren Zhang, Chao Song, Min Hou, Yuqing Yuan, Zhihao Ye, Zaixi Zhang, Sanshi Lei Yu:
AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking. - Parnian Kassraie, Nicolas Emmenegger, Andreas Krause, Aldo Pacchiano:
Anytime Model Selection in Linear Bandits. - Jiaqi Wang, Xingyi Yang, Suhan Cui, Liwei Che, Lingjuan Lyu, Dongkuan Xu, Fenglong Ma:
Towards Personalized Federated Learning via Heterogeneous Model Reassembly. - Xiaoming Shi, Siqiao Xue, Kangrui Wang, Fan Zhou, James Y. Zhang, Jun Zhou, Chenhao Tan, Hongyuan Mei:
Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning. - Tianyang Hu, Fei Chen, Haonan Wang, Jiawei Li, Wenjia Wang, Jiacheng Sun, Zhenguo Li:
Complexity Matters: Rethinking the Latent Space for Generative Modeling. - Ya-Ping Hsieh, Mohammad Reza Karimi Jaghargh, Andreas Krause, Panayotis Mertikopoulos:
Riemannian stochastic optimization methods avoid strict saddle points. - Sijia Zhou, Yunwen Lei, Ata Kabán:
Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms. - Gen Luo, Yiyi Zhou, Tianhe Ren, Shengxin Chen, Xiaoshuai Sun, Rongrong Ji:
Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models. - Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li:
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection. - Jerry Tang, Meng Du, Vy A. Vo, Vasudev Lal, Alexander Huth:
Brain encoding models based on multimodal transformers can transfer across language and vision. - Guangyan Chen, Meiling Wang, Yi Yang, Kai Yu, Li Yuan, Yufeng Yue:
PointGPT: Auto-regressively Generative Pre-training from Point Clouds. - Xiaoqian Wu, Yonglu Li, Jianhua Sun, Cewu Lu:
Symbol-LLM: Leverage Language Models for Symbolic System in Visual Human Activity Reasoning. - Sen Lin, Daouda Sow, Kaiyi Ji, Yingbin Liang, Ness B. Shroff:
Non-Convex Bilevel Optimization with Time-Varying Objective Functions. - Yigit Efe Erginbas, Thomas A. Courtade, Kannan Ramchandran, Soham Phade:
Online Pricing for Multi-User Multi-Item Markets. - Yu-Jie Zhang, Masashi Sugiyama:
Online (Multinomial) Logistic Bandit: Improved Regret and Constant Computation Cost. - John Isak Texas Falk, Luigi Bonati, Pietro Novelli, Michele Parrinello, Massimiliano Pontil:
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings. - Hava Chaptoukaev, Valeriya Strizhkova, Michele Panariello, Bianca Dalpaos, Aglind Reka, Valeria Manera, Susanne Thümmler, Esma Ismailova, Nicholas W. D. Evans, François Brémond, Massimiliano Todisco, Maria A. Zuluaga, Laura M. Ferrari:
StressID: a Multimodal Dataset for Stress Identification. - Qingxiu Dong, Jingjing Xu, Lingpeng Kong, Zhifang Sui, Lei Li:
Statistical Knowledge Assessment for Large Language Models. - Attila Lengyel, Ombretta Strafforello, Robert-Jan Bruintjes, Alexander Gielisse, Jan van Gemert:
Color Equivariant Convolutional Networks. - Erik R. Altman, Jovan Blanusa, Luc von Niederhäusern, Beni Egressy, Andreea Anghel, Kubilay Atasu:
Realistic Synthetic Financial Transactions for Anti-Money Laundering Models. - Zhiao Huang, Feng Chen, Yewen Pu, Chunru Lin, Hao Su, Chuang Gan:
DiffVL: Scaling Up Soft Body Manipulation using Vision-Language Driven Differentiable Physics. - Wentong Li, Yuqian Yuan, Song Wang, Wenyu Liu, Dongqi Tang, Jian Liu, Jianke Zhu, Lei Zhang:
Label-efficient Segmentation via Affinity Propagation. - Lei Ke, Mingqiao Ye, Martin Danelljan, Yifan Liu, Yu-Wing Tai, Chi-Keung Tang, Fisher Yu:
Segment Anything in High Quality. - Chirag Modi, Robert M. Gower, Charles Margossian, Yuling Yao, David M. Blei, Lawrence K. Saul:
Variational Inference with Gaussian Score Matching. - Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Feature Adaptation for Sparse Linear Regression. - Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, Mingsheng Long:
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling. - Guangyao Zhai, Evin Pinar Örnek, Shun-Cheng Wu, Yan Di, Federico Tombari, Nassir Navab, Benjamin Busam:
CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graphs. - Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto:
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. - Mingyuan Zhou, Tianqi Chen, Zhendong Wang, Huangjie Zheng:
Beta Diffusion. - Dat Do, Huy Nguyen, Khai Nguyen, Nhat Ho:
Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models. - Elad Hazan, Adam Tauman Kalai, Varun Kanade, Clara Mohri, Y. Jennifer Sun:
Partial Matrix Completion. - Dongxu Li, Junnan Li, Steven C. H. Hoi:
BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing. - Yiwen Kou, Zixiang Chen, Quanquan Gu:
Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data. - Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix X. Yu:
SpecTr: Fast Speculative Decoding via Optimal Transport. - Su Zheng, Haoyu Yang, Binwu Zhu, Bei Yu, Martin D. F. Wong:
LithoBench: Benchmarking AI Computational Lithography for Semiconductor Manufacturing. - Sanath Kumar Krishnamurthy, Ruohan Zhan, Susan Athey, Emma Brunskill:
Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization. - Sarah Toonsi, Jeff S. Shamma:
Higher-Order Uncoupled Dynamics Do Not Lead to Nash Equilibrium - Except When They Do. - Wenhu Chen, Hexiang Hu, Yandong Li, Nataniel Ruiz, Xuhui Jia, Ming-Wei Chang, William W. Cohen:
Subject-driven Text-to-Image Generation via Apprenticeship Learning. - Zhixun Li, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu:
GSLB: The Graph Structure Learning Benchmark. - Candice Schumann, Femi Olanubi, Auriel Wright, Ellis Monk Jr., Courtney Heldreth, Susanna Ricco:
Consensus and Subjectivity of Skin Tone Annotation for ML Fairness. - Ethan A. Brooks, Logan Walls, Richard L. Lewis, Satinder Singh:
Large Language Models can Implement Policy Iteration. - Junguang Jiang, Baixu Chen, Junwei Pan, Ximei Wang, Dapeng Liu, Jie Jiang, Mingsheng Long:
ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning. - Xinli Yue, Ningping Mou, Qian Wang, Lingchen Zhao:
Revisiting Adversarial Robustness Distillation from the Perspective of Robust Fairness. - Jiaqi Liu, Guoyang Xie, Ruitao Chen, Xinpeng Li, Jinbao Wang, Yong Liu, Chengjie Wang, Feng Zheng:
Real3D-AD: A Dataset of Point Cloud Anomaly Detection. - Lennert De Smet, Emanuele Sansone, Pedro Zuidberg Dos Martires:
Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick. - Ziyan Wang, Hao Wang:
Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing. - Tianyi Cheng, Dandan Shan, Ayda Hassen, Richard E. L. Higgins, David Fouhey:
Towards A Richer 2D Understanding of Hands at Scale. - Hussein Mozannar, Jimin J. Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag:
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding. - Bastian Boll, Christoph Schnörr:
On Certified Generalization in Structured Prediction. - Shane Bergsma, Timothy Zeyl, Lei Guo:
SutraNets: Sub-series Autoregressive Networks for Long-Sequence, Probabilistic Forecasting. - Jiaxin Bai, Xin Liu, Weiqi Wang, Chen Luo, Yangqiu Song:
Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints. - Zhuodong Yu, Ling Dai, Shaohang Xu, Siyang Gao, Chin Pang Ho:
Fast Bellman Updates for Wasserstein Distributionally Robust MDPs. - Jingying Gao, Qi Wu, Alan Blair, Maurice Pagnucco:
LoRA: A Logical Reasoning Augmented Dataset for Visual Question Answering. - Mengxiao Zhang, Yuheng Zhang, Olga Vrousgou, Haipeng Luo, Paul Mineiro:
Practical Contextual Bandits with Feedback Graphs. - Nate Rahn, Pierluca D'Oro, Harley Wiltzer, Pierre-Luc Bacon, Marc G. Bellemare:
Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control. - Yuechen Zhang, Jinbo Xing, Eric Lo, Jiaya Jia:
Real-World Image Variation by Aligning Diffusion Inversion Chain. - Alessandro Conti, Enrico Fini, Massimiliano Mancini, Paolo Rota, Yiming Wang, Elisa Ricci:
Vocabulary-free Image Classification. - Carlo Alfano, Rui Yuan, Patrick Rebeschini:
A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence. - Chunming He, Kai Li, Yachao Zhang, Guoxia Xu, Longxiang Tang, Yulun Zhang, Zhenhua Guo, Xiu Li:
Weakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Grouping. - Jincheng Mei, Bo Dai, Alekh Agarwal, Mohammad Ghavamzadeh, Csaba Szepesvári, Dale Schuurmans:
Ordering-based Conditions for Global Convergence of Policy Gradient Methods. - Berken Utku Demirel, Christian Holz:
Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning. - Peter Dixon, Aduri Pavan, Jason Vander Woude, N. V. Vinodchandran:
List and Certificate Complexities in Replicable Learning. - Van-Anh Nguyen, Tung-Long Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le:
Flat Seeking Bayesian Neural Networks. - Xin Liu, Zheng Li, Yifan Gao, Jingfeng Yang, Tianyu Cao, Zhengyang Wang, Bing Yin, Yangqiu Song:
Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns. - Heng Wang, Shangbin Feng, Tianxing He, Zhaoxuan Tan, Xiaochuang Han, Yulia Tsvetkov:
Can Language Models Solve Graph Problems in Natural Language? - Vuong Dinh An, Minh Nhat Vu, Toan Nguyen, Baoru Huang, Dzung Nguyen, Thieu Vo, Anh Nguyen:
Language-driven Scene Synthesis using Multi-conditional Diffusion Model. - Byeongchan Lee, Sehyun Lee:
Implicit Contrastive Representation Learning with Guided Stop-gradient. - Simone Papicchio, Paolo Papotti, Luca Cagliero:
QATCH: Benchmarking SQL-centric tasks with Table Representation Learning Models on Your Data. - Tiancheng Jin, Junyan Liu, Haipeng Luo:
Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms. - Jin Li, Yaoming Wang, Xiaopeng Zhang, Bowen Shi, Dongsheng Jiang, Chenglin Li, Wenrui Dai, Hongkai Xiong, Qi Tian:
AiluRus: A Scalable ViT Framework for Dense Prediction. - Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov:
CORL: Research-oriented Deep Offline Reinforcement Learning Library. - Aarush Gupta, Junli Cao, Chaoyang Wang, Ju Hu, Sergey Tulyakov, Jian Ren, László A. Jeni:
LightSpeed: Light and Fast Neural Light Fields on Mobile Devices. - Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf:
CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models. - Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis:
Riemannian Laplace approximations for Bayesian neural networks. - Cheng-Yu Hsieh, Jieyu Zhang, Zixian Ma, Aniruddha Kembhavi, Ranjay Krishna:
SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality. - Chen Sun, Wannan Yang, Thomas Jiralerspong, Dane Malenfant, Benjamin Alsbury-Nealy, Yoshua Bengio, Blake A. Richards:
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL. - Fang Wu, Stan Z. Li:
A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design. - Lawrence Stewart, Francis R. Bach, Felipe Llinares-López, Quentin Berthet:
Differentiable Clustering with Perturbed Spanning Forests. - Minbo Gao, Zhengfeng Ji, Tongyang Li, Qisheng Wang:
Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games. - Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio:
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. - Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li:
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models. - Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou:
Three Towers: Flexible Contrastive Learning with Pretrained Image Models. - Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham:
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models. - Dayou Yu, Weishi Shi, Qi Yu:
Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice. - Kai Zhang, Lingbo Mo, Wenhu Chen, Huan Sun, Yu Su:
MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing. - Raanan Y. Rohekar, Yaniv Gurwicz, Shami Nisimov:
Causal Interpretation of Self-Attention in Pre-Trained Transformers. - Eric Zelikman, Qian Huang, Gabriel Poesia, Noah D. Goodman, Nick Haber:
Parsel🦆: Algorithmic Reasoning with Language Models by Composing Decompositions. - Yuan Wang, Naisong Luo, Tianzhu Zhang:
Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentation. - Yihong Chen, Kelly Marchisio, Roberta Raileanu, David Ifeoluwa Adelani, Pontus Lars Erik Saito Stenetorp, Sebastian Riedel, Mikel Artetxe:
Improving Language Plasticity via Pretraining with Active Forgetting. - Yan Wang, Huaiqing Wu, Dan Nettleton:
Stability of Random Forests and Coverage of Random-Forest Prediction Intervals. - Xuchuang Wang, Qingyun Wu, Wei Chen, John C. S. Lui:
Multi-Fidelity Multi-Armed Bandits Revisited. - Liang Hou, Qi Cao, Yige Yuan, Songtao Zhao, Chongyang Ma, Siyuan Pan, Pengfei Wan, Zhongyuan Wang, Huawei Shen, Xueqi Cheng:
Augmentation-Aware Self-Supervision for Data-Efficient GAN Training. - Lukas Uzolas, Elmar Eisemann, Petr Kellnhofer:
Template-free Articulated Neural Point Clouds for Reposable View Synthesis. - Minoh Jeong, Martina Cardone, Alex Dytso:
Demystifying the Optimal Performance of Multi-Class Classification. - Chen Chen, Yuchen Hu, Chao-Han Huck Yang, Sabato Marco Siniscalchi, Pin-Yu Chen, Chng Eng Siong:
HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models. - Afra Amini, Li Du, Ryan Cotterell:
Structured Voronoi Sampling. - Miaoxi Zhu, Li Shen, Bo Du, Dacheng Tao:
Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm. - Annie Gray, Alexander Modell, Patrick Rubin-Delanchy, Nick Whiteley:
Hierarchical clustering with dot products recovers hidden tree structure. - Miltiadis Kofinas, Erik J. Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves:
Latent Field Discovery in Interacting Dynamical Systems with Neural Fields. - Dongyoung Kim, Jinwoo Shin, Pieter Abbeel, Younggyo Seo:
Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration. - Yuren Liu, Biwei Huang, Zhengmao Zhu, Hong-Long Tian, Mingming Gong, Yang Yu, Kun Zhang:
Learning World Models with Identifiable Factorization. - Gongjie Zhang, Jiahao Lin, Shuang Wu, Yilin Song, Zhipeng Luo, Yang Xue, Shijian Lu, Zuoguan Wang:
Online Map Vectorization for Autonomous Driving: A Rasterization Perspective. - Jiahui Lei, Congyue Deng, William B. Shen, Leonidas J. Guibas, Kostas Daniilidis:
NAP: Neural 3D Articulated Object Prior. - Bing Li, Jiaxin Chen, Xiuguo Bao, Di Huang:
Compressed Video Prompt Tuning. - Oren Mangoubi, Nisheeth K. Vishnoi:
Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk. - Yang Sui, Xin He, Yang Bai:
Implicit Regularization in Over-Parameterized Support Vector Machine. - Zirui Zhao, Wee Sun Lee, David Hsu:
Large Language Models as Commonsense Knowledge for Large-Scale Task Planning. - Yibo Jiang, Bryon Aragam, Victor Veitch:
Uncovering Meanings of Embeddings via Partial Orthogonality. - Ziqing Fan, Ruipeng Zhang, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang:
Federated Learning with Bilateral Curation for Partially Class-Disjoint Data. - Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel:
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model. - Wayne Soo, Vishwa Goudar, Xiao-Jing Wang:
Training biologically plausible recurrent neural networks on cognitive tasks with long-term dependencies. - Hyosoon Jang, Seonghyun Park, Sangwoo Mo, Sungsoo Ahn:
Diffusion Probabilistic Models for Structured Node Classification. - David Simchi-Levi, Chonghuan Wang, Zeyu Zheng:
Non-stationary Experimental Design under Linear Trends. - Zihang Shao, Xuanye Fang, Yaxin Li, Chaoran Feng, Jiangrong Shen, Qi Xu:
EICIL: Joint Excitatory Inhibitory Cycle Iteration Learning for Deep Spiking Neural Networks. - Owen Queen, Tom Hartvigsen, Teddy Koker, Huan He, Theodoros Tsiligkaridis, Marinka Zitnik:
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency. - Robert Tjarko Lange, Yujin Tang, Yingtao Tian:
NeuroEvoBench: Benchmarking Evolutionary Optimizers for Deep Learning Applications. - Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis:
HyTrel: Hypergraph-enhanced Tabular Data Representation Learning. - Peiqing Yang, Shangchen Zhou, Qingyi Tao, Chen Change Loy:
PGDiff: Guiding Diffusion Models for Versatile Face Restoration via Partial Guidance. - Qihang Yu, Ju He, Xueqing Deng, Xiaohui Shen, Liang-Chieh Chen:
Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP. - Jessica Dai, Paula Gradu, Christopher Harshaw:
CLIP-OGD: An Experimental Design for Adaptive Neyman Allocation in Sequential Experiments. - Lakshya A. Agrawal, Aditya Kanade, Navin Goyal, Shuvendu K. Lahiri, Sriram K. Rajamani:
Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context. - Zachary Charles, Nicole Mitchell, Krishna Pillutla, Michael Reneer, Zachary Garrett:
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning. - Vladimir Kostic, Karim Lounici, Pietro Novelli, Massimiliano Pontil:
Sharp Spectral Rates for Koopman Operator Learning. - Alane Suhr, Yoav Artzi:
Continual Learning for Instruction Following from Realtime Feedback. - Zuheng Xu, Trevor Campbell:
Embracing the chaos: analysis and diagnosis of numerical instability in variational flows. - Chengliang Liu, Jie Wen, Yabo Liu, Chao Huang, Zhihao Wu, Xiaoling Luo, Yong Xu:
Masked Two-channel Decoupling Framework for Incomplete Multi-view Weak Multi-label Learning. - Ioannis Panageas, Nikolas Patris, Stratis Skoulakis, Volkan Cevher:
Exponential Lower Bounds for Fictitious Play in Potential Games. - Minghui Hu, Jianbin Zheng, Daqing Liu, Chuanxia Zheng, Chaoyue Wang, Dacheng Tao, Tat-Jen Cham:
Cocktail: Mixing Multi-Modality Control for Text-Conditional Image Generation. - Chuning Zhu, Max Simchowitz, Siri Gadipudi, Abhishek Gupta:
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability. - Jialv Zou, Xinggang Wang, Jiahao Guo, Wenyu Liu, Qian Zhang, Chang Huang:
Circuit as Set of Points. - Wendong Liang, Armin Kekic, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf:
Causal Component Analysis. - Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, Yun Fu:
Latent Graph Inference with Limited Supervision. - Alexandre Verine, Benjamin Négrevergne, Muni Sreenivas Pydi, Yann Chevaleyre:
Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows. - Pawel A. Pierzchlewicz, Konstantin Willeke, Arne Nix, Pavithra Elumalai, Kelli Restivo, Tori Shinn, Cate Nealley, Gabrielle Rodriguez, Saumil S. Patel, Katrin Franke, Andreas S. Tolias, Fabian H. Sinz:
Energy Guided Diffusion for Generating Neurally Exciting Images. - Abdellah Aznag, Rachel Cummings, Adam N. Elmachtoub:
An active learning framework for multi-group mean estimation. - Ali Behrouz, Farnoosh Hashemi, Sadaf Sadeghian, Margo I. Seltzer:
CAT-Walk: Inductive Hypergraph Learning via Set Walks. - Maxence Noble, Valentin De Bortoli, Alain Durmus:
Unbiased constrained sampling with Self-Concordant Barrier Hamiltonian Monte Carlo. - Run Yang, Yuling Yang, Fan Zhou, Qiang Sun:
Directional diffusion models for graph representation learning. - Qiufu Li, Xi Jia, Jiancan Zhou, Linlin Shen, Jinming Duan:
UniTSFace: Unified Threshold Integrated Sample-to-Sample Loss for Face Recognition. - Zhaohan Xi, Tianyu Du, Changjiang Li, Ren Pang, Shouling Ji, Jinghui Chen, Fenglong Ma, Ting Wang:
Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks. - Xinyu Mao, Jiapeng Zhang:
On the Power of SVD in the Stochastic Block Model. - Jaewook J. Suh, Jisun Park, Ernest K. Ryu:
Continuous-time Analysis of Anchor Acceleration. - Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Rohin Shah:
BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks. - Görkay Aydemir, Weidi Xie, Fatma Güney:
Self-supervised Object-Centric Learning for Videos. - Qizhang Li, Yiwen Guo, Wangmeng Zuo, Hao Chen:
Improving Adversarial Transferability via Intermediate-level Perturbation Decay. - Hao Zheng, Hui Lin, Rong Zhao:
GUST: Combinatorial Generalization by Unsupervised Grouping with Neuronal Coherence. - Zhenghai Xue, Qingpeng Cai, Shuchang Liu, Dong Zheng, Peng Jiang, Kun Gai, Bo An:
State Regularized Policy Optimization on Data with Dynamics Shift. - Andy Zhou, Jindong Wang, Yu-Xiong Wang, Haohan Wang:
Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models. - Zitao Liu, Qiongqiong Liu, Teng Guo, Jiahao Chen, Shuyan Huang, Xiangyu Zhao, Jiliang Tang, Weiqi Luo, Jian Weng:
XES3G5M: A Knowledge Tracing Benchmark Dataset with Auxiliary Information. - Paul Pu Liang, Zihao Deng, Martin Q. Ma, James Y. Zou, Louis-Philippe Morency, Ruslan Salakhutdinov:
Factorized Contrastive Learning: Going Beyond Multi-view Redundancy. - Jungwoo Chae, Hyunin Cho, Sooyeon Go, Kyungmook Choi, Youngjung Uh:
Semantic Image Synthesis with Unconditional Generator. - Pengchong Hu, Zhizhong Han:
Learning Neural Implicit through Volume Rendering with Attentive Depth Fusion Priors. - Yifan Yang, Peiyao Xiao, Kaiyi Ji:
SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning. - Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos F. Psaros, Kenji Kawaguchi:
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification. - Fanqing Meng, Wenqi Shao, Zhanglin Peng, Chonghe Jiang, Kaipeng Zhang, Yu Qiao, Ping Luo:
Foundation Model is Efficient Multimodal Multitask Model Selector. - Marco Jiralerspong, Avishek Joey Bose, Ian Gemp, Chongli Qin, Yoram Bachrach, Gauthier Gidel:
Feature Likelihood Score: Evaluating the Generalization of Generative Models Using Samples. - Orr Zohar, Shih-Cheng Huang, Kuan-Chieh Wang, Serena Yeung:
LOVM: Language-Only Vision Model Selection. - Hao-Kai Zhang, Chenghong Zhu, Mingrui Jing, Xin Wang:
Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks. - Yuriy Biktairov, Jyotirmoy Deshmukh:
SOL: Sampling-based Optimal Linear bounding of arbitrary scalar functions. - Dibyadip Chatterjee, Fadime Sener, Shugao Ma, Angela Yao:
Opening the Vocabulary of Egocentric Actions. - Liang Chen, Shuming Ma, Dongdong Zhang, Furu Wei, Baobao Chang:
On the Pareto Front of Multilingual Neural Machine Translation. - Zhen Qin, Songlin Yang, Yiran Zhong:
Hierarchically Gated Recurrent Neural Network for Sequence Modeling. - Chirag Raman, Alec Nonnemaker, Amelia Villegas-Morcillo, Hayley Hung, Marco Loog:
Why Did This Model Forecast This Future? Information-Theoretic Saliency for Counterfactual Explanations of Probabilistic Regression Models. - Kai Liu, Zhihang Fu, Chao Chen, Sheng Jin, Ze Chen, Mingyuan Tao, Rongxin Jiang, Jieping Ye:
Category-Extensible Out-of-Distribution Detection via Hierarchical Context Descriptions. - Zhiyong Wang, Jize Xie, Tong Yu, Shuai Li, John C. S. Lui:
Online Corrupted User Detection and Regret Minimization. - Ayush Sawarni, Soumyabrata Pal, Siddharth Barman:
Nash Regret Guarantees for Linear Bandits. - Haoran You, Huihong Shi, Yipin Guo, Yingyan Lin:
ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer. - Angela Yuan, Chris Junchi Li, Gauthier Gidel, Michael I. Jordan, Quanquan Gu, Simon S. Du:
Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure. - Georgios Chionas, Dariusz R. Kowalski, Piotr Krysta:
Combinatorial Group Testing with Selfish Agents. - Wenchong He, Zhe Jiang, Tingsong Xiao, Zelin Xu, Shigang Chen, Ronald Fick, Miles Medina, Christine Angelini:
A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Space. - Michael Arbel, Romain Menegaux, Pierre Wolinski:
Rethinking Gauss-Newton for learning over-parameterized models. - Zepu Lu, Jin Chen, Defu Lian, Zaixi Zhang, Yong Ge, Enhong Chen:
Knowledge Distillation for High Dimensional Search Index. - Yu Cao, Jingrun Chen, Yixin Luo, Xiang Zhou:
Exploring the Optimal Choice for Generative Processes in Diffusion Models: Ordinary vs Stochastic Differential Equations. - Qianqian Xie, Weiguang Han, Xiao Zhang, Yanzhao Lai, Min Peng, Alejandro Lopez-Lira, Jimin Huang:
PIXIU: A Comprehensive Benchmark, Instruction Dataset and Large Language Model for Finance. - Shuhan Tan, Tushar Nagarajan, Kristen Grauman:
EgoDistill: Egocentric Head Motion Distillation for Efficient Video Understanding. - Weiduo Liao, Ying Wei, Mingchen Jiang, Qingfu Zhang, Hisao Ishibuchi:
Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework. - Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, Caroline Uhler:
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation. - Pascal Notin, Ruben Weitzman, Debora S. Marks, Yarin Gal:
ProteinNPT: Improving protein property prediction and design with non-parametric transformers. - Changho Shin, Sonia Cromp, Dyah Adila, Frederic Sala:
Mitigating Source Bias for Fairer Weak Supervision. - Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan:
GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels. - Runa Eschenhagen, Alexander Immer, Richard E. Turner, Frank Schneider, Philipp Hennig:
Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures. - Austin Tripp, Sergio Bacallado, Sukriti Singh, José Miguel Hernández-Lobato:
Tanimoto Random Features for Scalable Molecular Machine Learning. - Jean Tarbouriech, Tor Lattimore, Brendan O'Donoghue:
Probabilistic Inference in Reinforcement Learning Done Right. - Zhen Liu, Peitian Ma, Dongliang Chen, Wenbin Pei, Qianli Ma:
Scale-teaching: Robust Multi-scale Training for Time Series Classification with Noisy Labels. - Jiayi Guan, Guang Chen, Jiaming Ji, Long Yang, Ao Zhou, Zhijun Li, Changjun Jiang:
VOCE: Variational Optimization with Conservative Estimation for Offline Safe Reinforcement Learning. - Lasse Hansen, Nabeel Seedat, Mihaela van der Schaar, Andrija Petrovic:
Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark. - Mitchell Ostrow, Adam Eisen, Leo Kozachkov, Ila Fiete:
Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis. - Guanqiang Zhou, Ping Xu, Yue Wang, Zhi Tian:
H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets. - Jiachen T. Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal:
A Randomized Approach to Tight Privacy Accounting. - Kai Han, You Wu, He Huang, Shuang Cui:
Triple Eagle: Simple, Fast and Practical Budget-Feasible Mechanisms. - Sheng-Yen Chou, Pin-Yu Chen, Tsung-Yi Ho:
VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion Models. - Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun:
An Information Theory Perspective on Variance-Invariance-Covariance Regularization. - Xiaolong Zou, Zhikun Chu, Qinghai Guo, Jie Cheng, Bo Ho, Si Wu, Yuanyuan Mi:
Learning and processing the ordinal information of temporal sequences in recurrent neural circuits. - Zhong-Qiu Wang, Shinji Watanabe:
UNSSOR: Unsupervised Neural Speech Separation by Leveraging Over-determined Training Mixtures. - Yuankai Luo, Lei Shi, Veronika Thost:
Improving Self-supervised Molecular Representation Learning using Persistent Homology. - Zhongjie Yu, Martin Trapp, Kristian Kersting:
Characteristic Circuits. - Paul Rosa, Slava Borovitskiy, Alexander Terenin, Judith Rousseau:
Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds. - Jacy Reese Anthis, Victor Veitch:
Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness. - Congyue Deng, Jiahui Lei, William B. Shen, Kostas Daniilidis, Leonidas J. Guibas:
Banana: Banach Fixed-Point Network for Pointcloud Segmentation with Inter-Part Equivariance. - Zihao Wang, Shaofei Cai, Guanzhou Chen, Anji Liu, Xiaojian Ma, Yitao Liang:
Describe, Explain, Plan and Select: Interactive Planning with LLMs Enables Open-World Multi-Task Agents. - Yuheng Jia, Fuchao Yang, Yongqiang Dong:
Partial Label Learning with Dissimilarity Propagation guided Candidate Label Shrinkage. - Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang:
Data Selection for Language Models via Importance Resampling. - Gaurav Shrivastava, Ser Nam Lim, Abhinav Shrivastava:
Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements. - Ziyi Bai, Ruiping Wang, Xilin Chen:
Glance and Focus: Memory Prompting for Multi-Event Video Question Answering. - Max B. Paulus, Andreas Krause:
Learning To Dive In Branch And Bound. - Arash Ahmadian, Saurabh Dash, Hongyu Chen, Bharat Venkitesh, Stephen Zhen Gou, Phil Blunsom, Ahmet Üstün, Sara Hooker:
Intriguing Properties of Quantization at Scale. - Liang Yang, Runjie Shi, Qiuliang Zhang, Bingxin Niu, Zhen Wang, Xiaochun Cao, Chuan Wang:
Self-supervised Graph Neural Networks via Low-Rank Decomposition. - Erik Miehling, Rahul Nair, Elizabeth Daly, Karthikeyan Natesan Ramamurthy, Robert Redmond:
Cookie Consent Has Disparate Impact on Estimation Accuracy. - Saurav Jha, Dong Gong, He Zhao, Lina Yao:
NPCL: Neural Processes for Uncertainty-Aware Continual Learning. - Peter Shaw, Mandar Joshi, James Cohan, Jonathan Berant, Panupong Pasupat, Hexiang Hu, Urvashi Khandelwal, Kenton Lee, Kristina Toutanova:
From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces. - Gleb Novikov, David Steurer, Stefan Tiegel:
Robust Mean Estimation Without Moments for Symmetric Distributions. - Peter Macgregor:
Fast and Simple Spectral Clustering in Theory and Practice. - Xiuzhe Wu, Peng Dai, Weipeng Deng, Handi Chen, Yang Wu, Yan-Pei Cao, Ying Shan, Xiaojuan Qi:
CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation. - Ryan Kortvelesy, Steven D. Morad, Amanda Prorok:
Generalised f-Mean Aggregation for Graph Neural Networks. - Mahyar Fazlyab, Taha Entesari, Aniket Roy, Rama Chellappa:
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization. - Nils Sturma, Chandler Squires, Mathias Drton, Caroline Uhler:
Unpaired Multi-Domain Causal Representation Learning. - Haibao Yu, Yingjuan Tang, Enze Xie, Jilei Mao, Ping Luo, Zaiqing Nie:
Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection. - Zijian Li, Ruichu Cai, Guangyi Chen, Boyang Sun, Zhifeng Hao, Kun Zhang:
Subspace Identification for Multi-Source Domain Adaptation. - Sarath Sreedharan, Michael Katz:
Optimistic Exploration in Reinforcement Learning Using Symbolic Model Estimates. - Taiji Suzuki, Denny Wu, Kazusato Oko, Atsushi Nitanda:
Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond. - Yixiao Zhou, Ruiqi Jia, Hongxiang Lin, Hefeng Quan, Yumeng Zhao, Xiaoqing Lyu:
Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network. - Drago Plecko, Elias Bareinboim:
A Causal Framework for Decomposing Spurious Variations. - Tianjun Ke, Haoqun Cao, Zenan Ling, Feng Zhou:
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification. - Haitao Lin, Yufei Huang, Odin Zhang, Yunfan Liu, Lirong Wu, Siyuan Li, Zhiyuan Chen, Stan Z. Li:
Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration. - Ningyuan Huang, Ron Levie, Soledad Villar:
Approximately Equivariant Graph Networks. - Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen:
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. - Evren Gokcen, Anna Jasper, Alison Xu, Adam Kohn, Christian K. Machens, Byron M. Yu:
Uncovering motifs of concurrent signaling across multiple neuronal populations. - Jinxi Li, Ziyang Song, Bo Yang:
NVFi: Neural Velocity Fields for 3D Physics Learning from Dynamic Videos. - Leonardo Galli, Holger Rauhut, Mark Schmidt:
Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models. - Yiheng Zhu, Yang Zhan, Xuankun Huang, Yuwei Chen, Yujie Chen, Jiangwen Wei, Wei Feng, Yinzhi Zhou, Haoyuan Hu, Jieping Ye:
OFCOURSE: A Multi-Agent Reinforcement Learning Environment for Order Fulfillment. - Yulian Wu, Xingyu Zhou, Youming Tao, Di Wang:
On Private and Robust Bandits. - Siqi Shen, Chennan Ma, Chao Li, Weiquan Liu, Yongquan Fu, Songzhu Mei, Xinwang Liu, Cheng Wang:
RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization. - Jane H. Lee, Andre Wibisono, Emmanouil Zampetakis:
Learning Exponential Families from Truncated Samples. - Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew, Jiashi Feng, Mike Zheng Shou:
XAGen: 3D Expressive Human Avatars Generation. - Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine:
HIQL: Offline Goal-Conditioned RL with Latent States as Actions. - Haotian Liu, Chunyuan Li, Qingyang Wu, Yong Jae Lee:
Visual Instruction Tuning. - Rui Wang, Yanyan Ouyang, Panpan Yu, Wangli Xu:
A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging. - Bariscan Bozkurt, Cengiz Pehlevan, Alper T. Erdogan:
Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry. - Fnu Suya, Xiao Zhang, Yuan Tian, David Evans:
What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners? - Shirui Chen, Linxing Jiang, Rajesh P. N. Rao, Eric Shea-Brown:
Expressive probabilistic sampling in recurrent neural networks. - Thomas Steinke, Alexander Knop:
Counting Distinct Elements Under Person-Level Differential Privacy. - Feng Chen, Daniel Kunin, Atsushi Yamamura, Surya Ganguli:
Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks. - Liting Chen, Jie Yan, Zhengdao Shao, Lu Wang, Qingwei Lin, Saravanakumar Rajmohan, Thomas Moscibroda, Dongmei Zhang:
Conservative State Value Estimation for Offline Reinforcement Learning. - Xinyi Wu, Amir Ajorlou, Zihui Wu, Ali Jadbabaie:
Demystifying Oversmoothing in Attention-Based Graph Neural Networks. - Kenkun Liu, Derong Jin, Ailing Zeng, Xiaoguang Han, Lei Zhang:
A Comprehensive Benchmark for Neural Human Radiance Fields. - Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee:
Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms. - Erin George, Michael Murray, William Swartworth, Deanna Needell:
Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign? - Cyrille Kone, Emilie Kaufmann, Laura Richert:
Adaptive Algorithms for Relaxed Pareto Set Identification. - Jing Gu, Yilin Wang, Nanxuan Zhao, Tsu-Jui Fu, Wei Xiong, Qing Liu, Zhifei Zhang, He Zhang, Jianming Zhang, Hyunjoon Jung, Xin Eric Wang:
PHOTOSWAP: Personalized Subject Swapping in Images. - Ravid Shwartz-Ziv, Micah Goldblum, Yucen Lily Li, C. Bayan Bruss, Andrew Gordon Wilson:
Simplifying Neural Network Training Under Class Imbalance. - Johannes Kirschner, Seyed Alireza Bakhtiari, Kushagra Chandak, Volodymyr Tkachuk, Csaba Szepesvári:
Regret Minimization via Saddle Point Optimization. - Justin Whitehouse, Aaditya Ramdas, Zhiwei Steven Wu:
On the Sublinear Regret of GP-UCB. - Jun Yin, Chaozhuo Li, Hao Yan, Jianxun Lian, Senzhang Wang:
Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks. - Aaron Sidford, Chenyi Zhang:
Quantum speedups for stochastic optimization. - Zihao Wang, Lin Gui, Jeffrey Negrea, Victor Veitch:
Concept Algebra for (Score-Based) Text-Controlled Generative Models. - Guillaume Mahey, Laetitia Chapel, Gilles Gasso, Clément Bonet, Nicolas Courty:
Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics. - Kilian Pfeiffer, Ramin Khalili, Jörg Henkel:
Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices. - Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Sundararajan Sellamanickam, Ramakrishna Bairi:
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations. - Esmaeil Seraj, Jerry Xiong, Mariah Schrum, Matthew C. Gombolay:
Mixed-Initiative Multiagent Apprenticeship Learning for Human Training of Robot Teams. - Misha Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina Balcan, Kfir Y. Levy, Ron Meir, Zhiwei Steven Wu:
Meta-Learning Adversarial Bandit Algorithms. - Johann Brehmer, Pim de Haan, Sönke Behrends, Taco S. Cohen:
Geometric Algebra Transformer. - Qiang Ding, Yixuan Cao, Ping Luo:
Top-Ambiguity Samples Matter: Understanding Why Deep Ensemble Works in Selective Classification. - Amanda Bertsch, Uri Alon, Graham Neubig, Matthew R. Gormley:
Unlimiformer: Long-Range Transformers with Unlimited Length Input. - Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian:
Improving CLIP Training with Language Rewrites. - Tao Ge, Jing Hu, Li Dong, Shaoguang Mao, Yan Xia, Xun Wang, Si-Qing Chen, Furu Wei:
Extensible Prompts for Language Models on Zero-shot Language Style Customization. - Toru Lin, Allan Jabri:
MIMEx: Intrinsic Rewards from Masked Input Modeling. - Zhaolong Du, Shasha Mao, Yimeng Zhang, Shuiping Gou, Licheng Jiao, Lin Xiong:
RGMIL: Guide Your Multiple-Instance Learning Model with Regressor. - David Simchi-Levi, Zeyu Zheng, Feng Zhu:
Stochastic Multi-armed Bandits: Optimal Trade-off among Optimality, Consistency, and Tail Risk. - Siyu Jiao, Yunchao Wei, Yaowei Wang, Yao Zhao, Humphrey Shi:
Learning Mask-aware CLIP Representations for Zero-Shot Segmentation. - Mingze Wang, Chao Ma:
Understanding Multi-phase Optimization Dynamics and Rich Nonlinear Behaviors of ReLU Networks. - Zhen Qin, Rolf Jagerman, Rama Kumar Pasumarthi, Honglei Zhuang, He Zhang, Aijun Bai, Kai Hui, Le Yan, Xuanhui Wang:
RD-Suite: A Benchmark for Ranking Distillation. - Anastasia Koloskova, Ryan McKenna, Zachary Charles, John Keith Rush, H. Brendan McMahan:
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy. - David Loiseaux, Mathieu Carrière, Andrew J. Blumberg:
A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions. - Matt Deitke, Ruoshi Liu, Matthew Wallingford, Huong Ngo, Oscar Michel, Aditya Kusupati, Alan Fan, Christian Laforte, Vikram Voleti, Samir Yitzhak Gadre, Eli VanderBilt, Aniruddha Kembhavi, Carl Vondrick, Georgia Gkioxari, Kiana Ehsani, Ludwig Schmidt, Ali Farhadi:
Objaverse-XL: A Universe of 10M+ 3D Objects. - Shikai Qiu, Tim G. J. Rudner, Sanyam Kapoor, Andrew Gordon Wilson:
Should We Learn Most Likely Functions or Parameters? - Zongyi Li, Nikola B. Kovachki, Christopher B. Choy, Boyi Li, Jean Kossaifi, Shourya Prakash Otta, Mohammad Amin Nabian, Maximilian Stadler, Christian Hundt, Kamyar Azizzadenesheli, Animashree Anandkumar:
Geometry-Informed Neural Operator for Large-Scale 3D PDEs. - Xinyu Tang, Ashwinee Panda, Vikash Sehwag, Prateek Mittal:
Differentially Private Image Classification by Learning Priors from Random Processes. - Mohammad Reza Taesiri, Giang Nguyen, Sarra Habchi, Cor-Paul Bezemer, Anh Nguyen:
ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of Zoom and Spatial Biases in Image Classification. - Hyeong Kyu Choi, Seunghun Lee, Jaewon Chu, Hyunwoo J. Kim:
NuTrea: Neural Tree Search for Context-guided Multi-hop KGQA. - Adel Javanmard, Vahab Mirrokni:
Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization. - Jinpeng Chen, Runmin Cong, Yuxuan Luo, Horace Ho-Shing Ip, Sam Kwong:
Saving 100x Storage: Prototype Replay for Reconstructing Training Sample Distribution in Class-Incremental Semantic Segmentation. - Mayee F. Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré:
Skill-it! A data-driven skills framework for understanding and training language models. - Stefania Ionescu, Yuhao Du, Kenneth Joseph, Ancsa Hannak:
Strategic Behavior in Two-sided Matching Markets with Prediction-enhanced Preference-formation. - Tao Lin, Yiling Chen:
Sample Complexity of Forecast Aggregation. - Joey Hong, Sergey Levine, Anca D. Dragan:
Learning to Influence Human Behavior with Offline Reinforcement Learning. - Yuling Yao, Justin Domke:
Discriminative Calibration: Check Bayesian Computation from Simulations and Flexible Classifier. - Martijn de Vos, Sadegh Farhadkhani, Rachid Guerraoui, Anne-Marie Kermarrec, Rafael Pires, Rishi Sharma:
Epidemic Learning: Boosting Decentralized Learning with Randomized Communication. - Jingzhou Hu, Kejun Huang:
Global Identifiability of 𝓁1-based Dictionary Learning via Matrix Volume Optimization. - Jeonghoon Kim, Jung Hyun Lee, Sungdong Kim, Joonsuk Park, Kang Min Yoo, Se Jung Kwon, Dongsoo Lee:
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization. - Chenlu Ye, Rui Yang, Quanquan Gu, Tong Zhang:
Corruption-Robust Offline Reinforcement Learning with General Function Approximation. - Daniel Bertschinger, Christoph Hertrich, Paul Jungeblut, Tillmann Miltzow, Simon Weber:
Training Fully Connected Neural Networks is ∃R-Complete. - Hongzheng Yang, Cheng Chen, Yueyao Chen, Markus Scheppach, Hon-Chi Yip, Qi Dou:
Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization. - Zeren Tan, Yang Tian, Jian Li:
GLIME: General, Stable and Local LIME Explanation. - Jiaming Guo, Rui Zhang, Shaohui Peng, Qi Yi, Xing Hu, Ruizhi Chen, Zidong Du, Xishan Zhang, Ling Li, Qi Guo, Yunji Chen:
Efficient Symbolic Policy Learning with Differentiable Symbolic Expression. - Jiancong Xiao, Ruoyu Sun, Zhi-Quan Luo:
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization. - Kiarash Zahirnia, Yaochen Hu, Mark Coates, Oliver Schulte:
Neural Graph Generation from Graph Statistics. - Mohammadreza Pourreza, Davood Rafiei:
DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction. - Edward Raff, Amol Khanna, Fred Lu:
Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterations. - Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng:
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback. - Zhan Ling, Yunhao Fang, Xuanlin Li, Zhiao Huang, Mingu Lee, Roland Memisevic, Hao Su:
Deductive Verification of Chain-of-Thought Reasoning. - Anh Viet Do, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems. - Mathias Schreiner, Ole Winther, Simon Olsson:
Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics. - Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszar:
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data. - Zhongxiang Dai, Quoc Phong Nguyen, Sebastian Tay, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low, Patrick Jaillet:
Batch Bayesian Optimization For Replicable Experimental Design. - Siming Lan, Rui Zhang, Qi Yi, Jiaming Guo, Shaohui Peng, Yunkai Gao, Fan Wu, Ruizhi Chen, Zidong Du, Xing Hu, Xishan Zhang, Ling Li, Yunji Chen:
Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning. - Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei:
Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities. - Xiang Gu, Liwei Yang, Jian Sun, Zongben Xu:
Optimal Transport-Guided Conditional Score-Based Diffusion Model. - Hanlin Chen, Chen Li, Mengqi Guo, Zhiwen Yan, Gim Hee Lee:
GNeSF: Generalizable Neural Semantic Fields. - Jose H. Blanchet, Haoxuan Chen, Yiping Lu, Lexing Ying:
When can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality. - Alexandre Capone, Sandra Hirche, Geoff Pleiss:
Sharp Calibrated Gaussian Processes. - Takahiro Mimori, Michiaki Hamada:
GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies. - Chongyu Qu, Tiezheng Zhang, Hualin Qiao, Jie Liu, Yucheng Tang, Alan L. Yuille, Zongwei Zhou:
AbdomenAtlas-8K: Annotating 8, 000 CT Volumes for Multi-Organ Segmentation in Three Weeks. - Noam Wies, Yoav Levine, Amnon Shashua:
The Learnability of In-Context Learning. - Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, Omer Levy:
Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation. - Yanhui Guo, Xinxin Zuo, Peng Dai, Juwei Lu, Xiaolin Wu, Li Cheng, Youliang Yan, Songcen Xu, Xiaofei Wu:
Decorate3D: Text-Driven High-Quality Texture Generation for Mesh Decoration in the Wild. - Clayton Sanford, Daniel J. Hsu, Matus Telgarsky:
Representational Strengths and Limitations of Transformers. - Yanbang Wang, Jon M. Kleinberg:
On the Relationship Between Relevance and Conflict in Online Social Link Recommendations. - Ziba Parsons, Fei Dou, Houyi Du, Zheng Song, Jin Lu:
Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM. - Marco Rando, Cesare Molinari, Lorenzo Rosasco, Silvia Villa:
An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization. - Xinyi Chen, Elad Hazan:
Online Control for Meta-optimization. - Zixing Lei, Yiming Zhang, Yuxin Xiong, Siheng Chen:
Emergent Communication in Interactive Sketch Question Answering. - Swati Padmanabhan, David P. Woodruff, Richard Zhang:
Computing Approximate 𝓁p Sensitivities. - Momchil Peychev, Mark Niklas Müller, Marc Fischer, Martin T. Vechev:
Automated Classification of Model Errors on ImageNet. - Jihao Andreas Lin, Javier Antorán, Shreyas Padhy, David Janz, José Miguel Hernández-Lobato, Alexander Terenin:
Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent. - Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu:
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning. - Ammar Fayad, Majd Ibrahim:
On Slicing Optimality for Mutual Information. - Isabella Liu, Linghao Chen, Ziyang Fu, Liwen Wu, Haian Jin, Zhong Li, Chin Ming Ryan Wong, Yi Xu, Ravi Ramamoorthi, Zexiang Xu, Hao Su:
OpenIllumination: A Multi-Illumination Dataset for Inverse Rendering Evaluation on Real Objects. - Aleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, Adel Bibi:
Language Model Tokenizers Introduce Unfairness Between Languages. - Zhaolu Liu, Robert L. Peach, Pedro A. M. Mediano, Mauricio Barahona:
Interaction Measures, Partition Lattices and Kernel Tests for High-Order Interactions. - Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? - Yutong Xia, Yuxuan Liang, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann:
Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment. - Gergely Flamich:
Greedy Poisson Rejection Sampling. - Elias Nehme, Omer Yair, Tomer Michaeli:
Uncertainty Quantification via Neural Posterior Principal Components. - Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto:
Deep Reinforcement Learning with Plasticity Injection. - Hong-Sheng Zheng, Yu-Yuan Liu, Chen-Fong Hsu, Tsung Tai Yeh:
StreamNet: Memory-Efficient Streaming Tiny Deep Learning Inference on the Microcontroller. - Beepul Bharti, Paul H. Yi, Jeremias Sulam:
Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors. - Youquan Liu, Lingdong Kong, Jun Cen, Runnan Chen, Wenwei Zhang, Liang Pan, Kai Chen, Ziwei Liu:
Segment Any Point Cloud Sequences by Distilling Vision Foundation Models. - Giovanni de Felice, John Yannis Goulermas, Vladimir V. Gusev:
Time Series Kernels based on Nonlinear Vector AutoRegressive Delay Embeddings. - Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao:
SPA: A Graph Spectral Alignment Perspective for Domain Adaptation. - Yanfang Xue, Pengfei Fang, Jinyue Tian, Shipeng Zhu, Hui Xue:
CosNet: A Generalized Spectral Kernel Network. - Shafi Goldwasser, David F. Gruber, Adam Tauman Kalai, Orr Paradise:
A Theory of Unsupervised Translation Motivated by Understanding Animal Communication. - Lianghe Shi, Weiwei Liu:
Adversarial Self-Training Improves Robustness and Generalization for Gradual Domain Adaptation. - Guillem Simeon, Gianni De Fabritiis:
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials. - Chanwoo Park, Kaiqing Zhang, Asuman E. Ozdaglar:
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions. - Giulio Franzese, Giulio Corallo, Simone Rossi, Markus Heinonen, Maurizio Filippone, Pietro Michiardi:
Continuous-Time Functional Diffusion Processes. - Elena Sizikova, Niloufar Saharkhiz, Diksha Sharma, Miguel A. Lago, Berkman Sahiner, Jana G. Delfino, Aldo Badano:
Knowledge-based in silico models and dataset for the comparative evaluation of mammography AI for a range of breast characteristics, lesion conspicuities and doses. - Zian Li, Xiyuan Wang, Yinan Huang, Muhan Zhang:
Is Distance Matrix Enough for Geometric Deep Learning? - Qianyi Chen, Bo Li, Lu Deng, Yong Wang:
Optimized Covariance Design for AB Test on Social Network under Interference. - Susan Liang, Chao Huang, Yapeng Tian, Anurag Kumar, Chenliang Xu:
AV-NeRF: Learning Neural Fields for Real-World Audio-Visual Scene Synthesis. - Anton Voronov, Mikhail Khoroshikh, Artem Babenko, Max Ryabinin:
Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics. - Liunian Harold Li, Zi-Yi Dou, Nanyun Peng, Kai-Wei Chang:
DesCo: Learning Object Recognition with Rich Language Descriptions. - Gil Kur, Eli Putterman, Alexander Rakhlin:
On the Variance, Admissibility, and Stability of Empirical Risk Minimization. - Ulyana Piterbarg, Lerrel Pinto, Rob Fergus:
NetHack is Hard to Hack. - Benjamin Ellis, Jonathan Cook, Skander Moalla, Mikayel Samvelyan, Mingfei Sun, Anuj Mahajan, Jakob N. Foerster, Shimon Whiteson:
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning. - Yazhe Niu, Yuan Pu, Zhenjie Yang, Xueyan Li, Tong Zhou, Jiyuan Ren, Shuai Hu, Hongsheng Li, Yu Liu:
LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios. - Ling Yang, Jingwei Liu, Shenda Hong, Zhilong Zhang, Zhilin Huang, Zheming Cai, Wentao Zhang, Bin Cui:
Improving Diffusion-Based Image Synthesis with Context Prediction. - Yanxiang Ma, Minjing Dong, Chang Xu:
Adversarial Robustness through Random Weight Sampling. - Haithem Turki, Michael Zollhöfer, Christian Richardt, Deva Ramanan:
PyNeRF: Pyramidal Neural Radiance Fields. - Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou:
Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach. - Roi Livni:
Information Theoretic Lower Bounds for Information Theoretic Upper Bounds. - Siddhartha Laghuvarapu, Zhen Lin, Jimeng Sun:
CoDrug: Conformal Drug Property Prediction with Density Estimation under Covariate Shift. - Yiqun Chen, James Y. Zou:
TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter. - Berivan Isik, Wei-Ning Chen, Ayfer Özgür, Tsachy Weissman, Albert No:
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation. - Denys Rozumnyi, Stefan Popov, Kevis-Kokitsi Maninis, Matthias Nießner, Vittorio Ferrari:
Estimating Generic 3D Room Structures from 2D Annotations. - Sungbin Lim, Eun-Bi Yoon, Taehyun Byun, Taewon Kang, Seungwoo Kim, Kyungjae Lee, Sungjoon Choi:
Score-based Generative Modeling through Stochastic Evolution Equations in Hilbert Spaces. - Thomas Fel, Thibaut Boissin, Victor Boutin, Agustin Picard, Paul Novello, Julien Colin, Drew Linsley, Tom Rousseau, Rémi Cadène, Lore Goetschalckx, Laurent Gardes, Thomas Serre:
Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization. - Maximilien Dreveton, Felipe S. Fernandes, Daniel R. Figueiredo:
Exact recovery and Bregman hard clustering of node-attributed Stochastic Block Model. - Mateo Espinosa Zarlenga, Katie Collins, Krishnamurthy Dvijotham, Adrian Weller, Zohreh Shams, Mateja Jamnik:
Learning to Receive Help: Intervention-Aware Concept Embedding Models. - David Lindner, János Kramár, Sebastian Farquhar, Matthew Rahtz, Tom McGrath, Vladimir Mikulik:
Tracr: Compiled Transformers as a Laboratory for Interpretability. - Truong Thao Nguyen, Balazs Gerofi, Edgar Josafat Martinez-Noriega, François Trahay, Mohamed Wahib:
KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training. - Dapeng Hu, Jian Liang, Jun Hao Liew, Chuhui Xue, Song Bai, Xinchao Wang:
Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation. - Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos, Jose H. Blanchet:
Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games. - Jin Xu, Emilien Dupont, Kaspar Märtens, Thomas Rainforth, Yee Whye Teh:
Deep Stochastic Processes via Functional Markov Transition Operators. - Wisdom Oluchi Ikezogwo, Mehmet Saygin Seyfioglu, Fatemeh Ghezloo, Dylan Stefan Chan Geva, Fatwir Sheikh Mohammed, Pavan Kumar Anand, Ranjay Krishna, Linda G. Shapiro:
Quilt-1M: One Million Image-Text Pairs for Histopathology. - Alexander Tyurin, Peter Richtárik:
A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting. - Bhavya Sukhija, Lenart Treven, Cansu Sancaktar, Sebastian Blaes, Stelian Coros, Andreas Krause:
Optimistic Active Exploration of Dynamical Systems. - Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li, Weiming Lu, Yueting Zhuang:
HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face. - Lucas Nunes Alegre, Ana L. C. Bazzan, Ann Nowé, Bruno C. da Silva:
Multi-Step Generalized Policy Improvement by Leveraging Approximate Models. - Sima Behpour, Thang Long Doan, Xin Li, Wenbin He, Liang Gou, Liu Ren:
GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients. - Thomas Schmied, Markus Hofmarcher, Fabian Paischer, Razvan Pascanu, Sepp Hochreiter:
Learning to Modulate pre-trained Models in RL. - Ruijia Wang, YiWu Sun, Yujie Luo, Shaochuan Li, Cheng Yang, Xingyi Cheng, Hui Li, Chuan Shi, Le Song:
Injecting Multimodal Information into Rigid Protein Docking via Bi-level Optimization. - Xiaoshuai Hao, Wanqian Zhang:
Uncertainty-Aware Alignment Network for Cross-Domain Video-Text Retrieval. - Jialu Gao, Kaizhe Hu, Guowei Xu, Huazhe Xu:
Can Pre-Trained Text-to-Image Models Generate Visual Goals for Reinforcement Learning? - Yuzhong Wang, Xu Han, Weilin Zhao, Guoyang Zeng, Zhiyuan Liu, Maosong Sun:
H3T: Efficient Integration of Memory Optimization and Parallelism for Large-scale Transformer Training. - Yuanhao Cai, Yuxin Zheng, Jing Lin, Xin Yuan, Yulun Zhang, Haoqian Wang:
Binarized Spectral Compressive Imaging. - Joe Suk, Arpit Agarwal:
When Can We Track Significant Preference Shifts in Dueling Bandits? - Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong:
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization. - Jianyou Wang, Kaicheng Wang, Xiaoyue Wang, Prudhviraj Naidu, Leon Bergen, Ramamohan Paturi:
Scientific Document Retrieval using Multi-level Aspect-based Queries. - Mert Yüksekgönül, Linjun Zhang, James Y. Zou, Carlos Guestrin:
Beyond Confidence: Reliable Models Should Also Consider Atypicality. - Anthony Gruber, Kookjin Lee, Nathaniel Trask:
Reversible and irreversible bracket-based dynamics for deep graph neural networks. - Yuzhou Cao, Hussein Mozannar, Lei Feng, Hongxin Wei, Bo An:
In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer. - Linyan Huang, Zhiqi Li, Chonghao Sima, Wenhai Wang, Jingdong Wang, Yu Qiao, Hongyang Li:
Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detection. - Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo:
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions. - Lukasz Augustyniak, Szymon Wozniak, Marcin Gruza, Piotr Gramacki, Krzysztof Rajda, Mikolaj Morzy, Tomasz Kajdanowicz:
Massively Multilingual Corpus of Sentiment Datasets and Multi-faceted Sentiment Classification Benchmark. - Hyeonjeong Ha, Minseon Kim, Sung Ju Hwang:
Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations. - Manan Tomar, Riashat Islam, Matthew E. Taylor, Sergey Levine, Philip Bachman:
Ignorance is Bliss: Robust Control via Information Gating. - Shutong Ding, Jingya Wang, Yali Du, Ye Shi:
Reduced Policy Optimization for Continuous Control with Hard Constraints. - Mingyu Xu, Zheng Lian, Lei Feng, Bin Liu, Jianhua Tao:
ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning. - Hyunsoo Lee, Minsoo Kang, Bohyung Han:
Conditional Score Guidance for Text-Driven Image-to-Image Translation. - Vinay Shukla, Zhe Zeng, Kareem Ahmed, Guy Van den Broeck:
A Unified Approach to Count-Based Weakly Supervised Learning. - Kaiyue Wen, Yuchen Li, Bingbin Liu, Andrej Risteski:
Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars. - Mingjie Li, Yisen Wang, Zhouchen Lin:
GEQ: Gaussian Kernel Inspired Equilibrium Models. - Yiming Wang, Ming Yang, Renzhi Dong, Binbin Sun, Furui Liu, Leong Hou U:
Efficient Potential-based Exploration in Reinforcement Learning using Inverse Dynamic Bisimulation Metric. - Joy Hsu, Jiayuan Mao, Joshua B. Tenenbaum, Jiajun Wu:
What's Left? Concept Grounding with Logic-Enhanced Foundation Models. - Ke Jiang, Jia-Yu Yao, Xiaoyang Tan:
Recovering from Out-of-sample States via Inverse Dynamics in Offline Reinforcement Learning. - Li-Wei H. Lehman, Benjamin Moody, Harsh Deep, Feng Wu, Hasan Saeed, Lucas McCullum, Diane Perry, Tristan Struja, Qiao Li, Gari D. Clifford, Roger G. Mark:
VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors. - Rongkun Zheng, Lu Qi, Xi Chen, Yi Wang, Kun Wang, Yu Qiao, Hengshuang Zhao:
TMT-VIS: Taxonomy-aware Multi-dataset Joint Training for Video Instance Segmentation. - Yale Song, Eugene Byrne, Tushar Nagarajan, Huiyu Wang, Miguel Martin, Lorenzo Torresani:
Ego4D Goal-Step: Toward Hierarchical Understanding of Procedural Activities. - Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang:
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. - Xiaoyuan Zhang, Xi Lin, Bo Xue, Yifan Chen, Qingfu Zhang:
Hypervolume Maximization: A Geometric View of Pareto Set Learning. - Koen Minartz, Yoeri Poels, Simon M. Koop, Vlado Menkovski:
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics. - Fereshte Khani, Marco Túlio Ribeiro:
Collaborative Alignment of NLP Models. - Karthik Valmeekam, Matthew Marquez, Alberto Olmo Hernandez, Sarath Sreedharan, Subbarao Kambhampati:
PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change. - Yule Wang, Zijing Wu, Chengrui Li, Anqi Wu:
Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Model. - Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen:
Closing the gap between the upper bound and lower bound of Adam's iteration complexity. - Zachary Teed, Lahav Lipson, Jia Deng:
Deep Patch Visual Odometry. - Mehran Kazemi, Quan Yuan, Deepti Bhatia, Najoung Kim, Xin Xu, Vaiva Imbrasaite, Deepak Ramachandran:
BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information. - In Huh, Changwook Jeong, Jae Myung Choe, Younggu Kim, Daesin Kim:
Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning. - Shuzheng Si, Wentao Ma, Haoyu Gao, Yuchuan Wu, Ting-En Lin, Yinpei Dai, Hangyu Li, Rui Yan, Fei Huang, Yongbin Li:
SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents. - Atsuki Sato, Yusuke Matsui:
Fast Partitioned Learned Bloom Filter. - Wenjie Qiu, Wensen Mao, He Zhu:
Instructing Goal-Conditioned Reinforcement Learning Agents with Temporal Logic Objectives. - Jinbiao Chen, Zizhen Zhang, Zhiguang Cao, Yaoxin Wu, Yining Ma, Te Ye, Jiahai Wang:
Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement. - Youpeng Zhao, Yaodong Yang, Zhenbo Lu, Wengang Zhou, Houqiang Li:
Multi-Agent First Order Constrained Optimization in Policy Space. - Chiyu Ma, Brandon Zhao, Chaofan Chen, Cynthia Rudin:
This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations. - Sehoon Kim, Karttikeya Mangalam, Suhong Moon, Jitendra Malik, Michael W. Mahoney, Amir Gholami, Kurt Keutzer:
Speculative Decoding with Big Little Decoder. - Eduard Tulchinskii, Kristian Kuznetsov, Laida Kushnareva, Daniil Cherniavskii, Sergey I. Nikolenko, Evgeny Burnaev, Serguei Barannikov, Irina Piontkovskaya:
Intrinsic Dimension Estimation for Robust Detection of AI-Generated Texts. - Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou:
Replicable Clustering. - Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramèr, Nicholas Carlini:
Counterfactual Memorization in Neural Language Models. - Sili Huang, Yanchao Sun, Jifeng Hu, Siyuan Guo, Hechang Chen, Yi Chang, Lichao Sun, Bo Yang:
Learning Generalizable Agents via Saliency-guided Features Decorrelation. - Yang He, Lingao Xiao, Joey Tianyi Zhou:
You Only Condense Once: Two Rules for Pruning Condensed Datasets. - Roberto Cipollone, Anders Jonsson, Alessandro Ronca, Mohammad Sadegh Talebi:
Provably Efficient Offline Reinforcement Learning in Regular Decision Processes. - Jiarui Hu, Mao Mao, Hujun Bao, Guofeng Zhang, Zhaopeng Cui:
CP-SLAM: Collaborative Neural Point-based SLAM System. - Saurabh Saxena, Charles Herrmann, Junhwa Hur, Abhishek Kar, Mohammad Norouzi, Deqing Sun, David J. Fleet:
The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation. - Ilias Diakonikolas, Daniel Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis:
Efficient Testable Learning of Halfspaces with Adversarial Label Noise. - Yifan Yang, Peiyao Xiao, Kaiyi Ji:
Achieving O(ε-1.5) Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization. - Nicholas Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R. Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang:
Robust and Actively Secure Serverless Collaborative Learning. - Hanyang Peng, Shuang Qin, Yue Yu, Jin Wang, Hui Wang, Ge Li:
Birder: Communication-Efficient 1-bit Adaptive Optimizer for Practical Distributed DNN Training. - Nicolas Menet, Michael Hersche, Geethan Karunaratne, Luca Benini, Abu Sebastian, Abbas Rahimi:
MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition. - Xiaoyu Liu, Jiaxin Yuan, Bang An, Yuancheng Xu, Yifan Yang, Furong Huang:
C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder. - Thalles Santos Silva, Adín Ramírez Rivera:
Representation Learning via Consistent Assignment of Views over Random Partitions. - Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma:
Federated Multi-Objective Learning. - Ruibin Yuan, Yinghao Ma, Yizhi Li, Ge Zhang, Xingran Chen, Hanzhi Yin, Le Zhuo, Yiqi Liu, Jiawen Huang, Zeyue Tian, Binyue Deng, Ningzhi Wang, Chenghua Lin, Emmanouil Benetos, Anton Ragni, Norbert Gyenge, Roger B. Dannenberg, Wenhu Chen, Gus Xia, Wei Xue, Si Liu, Shi Wang, Ruibo Liu, Yike Guo, Jie Fu:
MARBLE: Music Audio Representation Benchmark for Universal Evaluation. - Geunwoo Kim, Pierre Baldi, Stephen McAleer:
Language Models can Solve Computer Tasks. - Gaku Morio, Christopher D. Manning:
An NLP Benchmark Dataset for Assessing Corporate Climate Policy Engagement. - Poorya Mianjy, Raman Arora:
Robustness Guarantees for Adversarially Trained Neural Networks. - Jialong Wu, Haoyu Ma, Chaoyi Deng, Mingsheng Long:
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning. - Daniel Halpern, Rachel Li, Ariel D. Procaccia:
Strategyproof Voting under Correlated Beliefs. - Hang Lou, Siran Li, Hao Ni:
PCF-GAN: generating sequential data via the characteristic function of measures on the path space. - Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch:
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods. - Khai Nguyen, Tongzheng Ren, Nhat Ho:
Markovian Sliced Wasserstein Distances: Beyond Independent Projections. - Changyu Chen, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha, Pradeep Varakantham:
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning. - Amir Joudaki, Hadi Daneshmand, Francis R. Bach:
On the impact of activation and normalization in obtaining isometric embeddings at initialization. - Zhenyu Wang, Ya-Li Li, Xi Chen, Hengshuang Zhao, Shengjin Wang:
Uni3DETR: Unified 3D Detection Transformer. - Rafail Fridman, Amit Abecasis, Yoni Kasten, Tali Dekel:
SceneScape: Text-Driven Consistent Scene Generation. - Ori Press, Steffen Schneider, Matthias Kümmerer, Matthias Bethge:
RDumb: A simple approach that questions our progress in continual test-time adaptation. - Parikshit Gopalan, Michael P. Kim, Omer Reingold:
Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration. - Tong Wu, Zhihao Fan, Xiao Liu, Hai-Tao Zheng, Yeyun Gong, Yelong Shen, Jian Jiao, Juntao Li, Zhongyu Wei, Jian Guo, Nan Duan, Weizhu Chen:
AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation. - Tsai Hor Chan, Kin Wai Lau, Jiajun Shen, Guosheng Yin, Lequan Yu:
Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations. - Ziye Ma, Javad Lavaei, Somayeh Sojoudi:
Algorithmic Regularization in Tensor Optimization: Towards a Lifted Approach in Matrix Sensing. - Dian Wang, Xupeng Zhu, Jung Yeon Park, Mingxi Jia, Guanang Su, Robert Platt, Robin Walters:
A General Theory of Correct, Incorrect, and Extrinsic Equivariance. - Martina G. Vilas, Timothy Schaumlöffel, Gemma Roig:
Analyzing Vision Transformers for Image Classification in Class Embedding Space. - Bingliang Jiao, Lingqiao Liu, Liying Gao, Ruiqi Wu, Guosheng Lin, Peng Wang, Yanning Zhang:
Toward Re-Identifying Any Animal. - Darshil Doshi, Tianyu He, Andrey Gromov:
Critical Initialization of Wide and Deep Neural Networks using Partial Jacobians: General Theory and Applications. - Mathieu Molina, Nicolas Gast, Patrick Loiseau, Vianney Perchet:
Trading-off price for data quality to achieve fair online allocation. - Youngsoo Baek, Samuel Berchuck, Sayan Mukherjee:
Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression. - Marie Maros, Gesualdo Scutari:
Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence. - Michael Beukman, Devon Jarvis, Richard Klein, Steven James, Benjamin Rosman:
Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies. - Ruiqi Zhong, Peter Zhang, Steve Li, Jinwoo Ahn, Dan Klein, Jacob Steinhardt:
Goal Driven Discovery of Distributional Differences via Language Descriptions. - Haochuan Li, Jian Qian, Yi Tian, Alexander Rakhlin, Ali Jadbabaie:
Convex and Non-convex Optimization Under Generalized Smoothness. - Wenxin Tai, Yue Lei, Fan Zhou, Goce Trajcevski, Ting Zhong:
DOSE: Diffusion Dropout with Adaptive Prior for Speech Enhancement. - Ren Li, Benoît Guillard, Pascal Fua:
ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns. - Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath:
Optimality of Message-Passing Architectures for Sparse Graphs. - Zhun Deng, Thomas P. Zollo, Jake Snell, Toniann Pitassi, Richard S. Zemel:
Distribution-Free Statistical Dispersion Control for Societal Applications. - Jaemin Na, Jung-Woo Ha, Hyung Jin Chang, Dongyoon Han, Wonjun Hwang:
Switching Temporary Teachers for Semi-Supervised Semantic Segmentation. - Milena Gazdieva, Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev:
Extremal Domain Translation with Neural Optimal Transport. - Yijia Cheng, Xin Liu, Jingyu Yang:
Recaptured Raw Screen Image and Video Demoiréing via Channel and Spatial Modulations. - Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Laurière, Matthieu Geist:
On Imitation in Mean-field Games. - Yingjie Wang, Jiajun Deng, Yuenan Hou, Yao Li, Yu Zhang, Jianmin Ji, Wanli Ouyang, Yanyong Zhang:
CluB: Cluster Meets BEV for LiDAR-Based 3D Object Detection. - Nathanael Bosch, Philipp Hennig, Filip Tronarp:
Probabilistic Exponential Integrators. - Yiwei Lu, Yaoliang Yu, Xinlin Li, Vahid Partovi Nia:
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers. - Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. - Yixing Lao, Xiaogang Xu, Zhipeng Cai, Xihui Liu, Hengshuang Zhao:
CorresNeRF: Image Correspondence Priors for Neural Radiance Fields. - François Rozet, Gilles Louppe:
Score-based Data Assimilation. - Jinhwan Sul, Jihoon Han, Joonseok Lee:
Mr. HiSum: A Large-scale Dataset for Video Highlight Detection and Summarization. - Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel:
Sharp Bounds for Generalized Causal Sensitivity Analysis. - Yixiu Mao, Hongchang Zhang, Chen Chen, Yi Xu, Xiangyang Ji:
Supported Value Regularization for Offline Reinforcement Learning. - Yingying Fan, Yu Wu, Bo Du, Yutian Lin:
Revisit Weakly-Supervised Audio-Visual Video Parsing from the Language Perspective. - Asanobu Kitamoto, Jared Hwang, Bastien Vuillod, Lucas Gautier, Yingtao Tian, Tarin Clanuwat:
Digital Typhoon: Long-term Satellite Image Dataset for the Spatio-Temporal Modeling of Tropical Cyclones. - Lorenzo Brusca, Lars C. P. M. Quaedvlieg, Stratis Skoulakis, Grigorios Chrysos, Volkan Cevher:
Maximum Independent Set: Self-Training through Dynamic Programming. - Edward Kim, Yohan Karunanayake, Hanna Kurniawati:
Reference-Based POMDPs. - Agrim Gupta, Jiajun Wu, Jia Deng, Fei-Fei Li:
Siamese Masked Autoencoders. - Eun-Bi Yoon, Keehun Park, Sungwoong Kim, Sungbin Lim:
Score-based Generative Models with Lévy Processes. - Mohamed El Amine Boudjoghra, Salwa K. Al Khatib, Jean Lahoud, Hisham Cholakkal, Rao Muhammad Anwer, Salman H. Khan, Fahad Shahbaz Khan:
3D Indoor Instance Segmentation in an Open-World. - Karolis Martinkus, Jan Ludwiczak, Wei-Ching Liang, Julien Lafrance-Vanasse, Isidro Hötzel, Arvind Rajpal, Yan Wu, Kyunghyun Cho, Richard Bonneau, Vladimir Gligorijevic, Andreas Loukas:
AbDiffuser: full-atom generation of in-vitro functioning antibodies. - Xitong Liang, Alberto Caron, Samuel Livingstone, Jim E. Griffin:
Structure Learning with Adaptive Random Neighborhood Informed MCMC. - Yi Ma, Hongyao Tang, Dong Li, Zhaopeng Meng:
Reining Generalization in Offline Reinforcement Learning via Representation Distinction. - Xuan Chen, Wenbo Guo, Guanhong Tao, Xiangyu Zhang, Dawn Song:
BIRD: Generalizable Backdoor Detection and Removal for Deep Reinforcement Learning. - Yijun Dong, Kevin Miller, Qi Lei, Rachel Ward:
Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering. - Siddharth Prasad, Maria-Florina Balcan, Tuomas Sandholm:
Bicriteria Multidimensional Mechanism Design with Side Information. - Klemen Kotar, Stephen Tian, Hong-Xing Yu, Dan Yamins, Jiajun Wu:
Are These the Same Apple? Comparing Images Based on Object Intrinsics. - Adarsh Pyarelal, Eric Duong, Caleb Shibu, Paulo Soares, Savannah Boyd, Payal Khosla, Valeria A. Pfeifer, Diheng Zhang, Eric Andrews, Rick Champlin, Vincent Raymond, Meghavarshini Krishnaswamy, Clayton T. Morrison, Emily Butler, Kobus Barnard:
The ToMCAT Dataset. - Xu Yang, Yongliang Wu, Mingzhuo Yang, Haokun Chen, Xin Geng:
Exploring Diverse In-Context Configurations for Image Captioning. - Youngjoong Kwon, Lingjie Liu, Henry Fuchs, Marc Habermann, Christian Theobalt:
DELIFFAS: Deformable Light Fields for Fast Avatar Synthesis. - Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt:
Zero-Shot Anomaly Detection via Batch Normalization. - Yotam Alexander, Nimrod De La Vega, Noam Razin, Nadav Cohen:
What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement. - Qiong Wu, Wei Yu, Yiyi Zhou, Shubin Huang, Xiaoshuai Sun, Rongrong Ji:
Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models. - Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause:
A Dynamical System View of Langevin-Based Non-Convex Sampling. - Jiachang Liu, Sam Rosen, Chudi Zhong, Cynthia Rudin:
OKRidge: Scalable Optimal k-Sparse Ridge Regression. - Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. - Dongrui Liu, Huiqi Deng, Xu Cheng, Qihan Ren, Kangrui Wang, Quanshi Zhang:
Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities. - Thien Le, Stefanie Jegelka:
Limits, approximation and size transferability for GNNs on sparse graphs via graphops. - Natalie Frank, Jonathan Niles-Weed:
The Adversarial Consistency of Surrogate Risks for Binary Classification. - Andreas Östling, Holli Sargeant, Huiyuan Xie, Ludwig Bull, Alexander Terenin, Leif Jonsson, Måns Magnusson, Felix Steffek:
The Cambridge Law Corpus: A Corpus for Legal AI Research. - Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis:
Large Language Models of Code Fail at Completing Code with Potential Bugs. - Banghua Zhu, Mingyu Ding, Philip L. Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao:
Doubly-Robust Self-Training. - Zheng Zhang, Qi Liu, Hao Jiang, Fei Wang, Yan Zhuang, Le Wu, Weibo Gao, Enhong Chen:
FairLISA: Fair User Modeling with Limited Sensitive Attributes Information. - Kenneth Li, Oam Patel, Fernanda B. Viégas, Hanspeter Pfister, Martin Wattenberg:
Inference-Time Intervention: Eliciting Truthful Answers from a Language Model. - Siddharth Gollapudi, Sepideh Mahabadi, Varun Sivashankar:
Composable Coresets for Determinant Maximization: Greedy is Almost Optimal. - Jieming Cui, Ziren Gong, Baoxiong Jia, Siyuan Huang, Zilong Zheng, Jianzhu Ma, Yixin Zhu:
ProBio: A Protocol-guided Multimodal Dataset for Molecular Biology Lab. - Mazda Moayeri, Wenxiao Wang, Sahil Singla, Soheil Feizi:
Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases. - Seokil Ham, Jungwuk Park, Dong-Jun Han, Jaekyun Moon:
NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks. - Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, James Xu Zhao, Min-Yen Kan, Junxian He, Michael Qizhe Xie:
Self-Evaluation Guided Beam Search for Reasoning. - Ayush Pande, Gaurav Sharma:
ViSt3D: Video Stylization with 3D CNN. - Adam Block, Max Simchowitz, Russ Tedrake:
Smoothed Online Learning for Prediction in Piecewise Affine Systems. - Jinhang Zuo, Zhiyao Zhang, Zhiyong Wang, Shuai Li, Mohammad Hajiesmaili, Adam Wierman:
Adversarial Attacks on Online Learning to Rank with Click Feedback. - Zeyue Xue, Guanglu Song, Qiushan Guo, Boxiao Liu, Zhuofan Zong, Yu Liu, Ping Luo:
RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Paths. - Qizhang Li, Yiwen Guo, Wangmeng Zuo, Hao Chen:
Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly. - Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. - Fulton Wang, Julius Adebayo, Sarah Tan, Diego García-Olano, Narine Kokhlikyan:
Error Discovery By Clustering Influence Embeddings. - Bin Huang, Jiaqian Yu, Yiwei Chen, Siyang Pan, Qiang Wang, Zhi Wang:
BadTrack: A Poison-Only Backdoor Attack on Visual Object Tracking. - Dayong Ren, Zhe Ma, Yuanpei Chen, Weihang Peng, Xiaode Liu, Yuhan Zhang, Yufei Guo:
Spiking PointNet: Spiking Neural Networks for Point Clouds. - Ranran Shen, Pan Peng:
A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time. - Richard Nock, Ehsan Amid, Manfred K. Warmuth:
Boosting with Tempered Exponential Measures. - Hua Wang, Sheng Gao, Huanyu Zhang, Weijie J. Su, Milan Shen:
DP-HyPO: An Adaptive Private Framework for Hyperparameter Optimization. - Christian Lange, Elijah Cole, Grant Van Horn, Oisin Mac Aodha:
Active Learning-Based Species Range Estimation. - Zhengyang Geng, Ashwini Pokle, J. Zico Kolter:
One-Step Diffusion Distillation via Deep Equilibrium Models. - Yossi Azar, Debmalya Panigrahi, Noam Touitou:
Discrete-Smoothness in Online Algorithms with Predictions. - Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bayan Bruss, Andrew Gordon Wilson, Tom Goldstein, Micah Goldblum:
A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning. - Zihao Hu, Guanghui Wang, Jacob D. Abernethy:
Riemannian Projection-free Online Learning. - Peter Yongho Kim, Junbeom Kwon, Sunghwan Joo, Sangyoon Bae, Donggyu Lee, Yoonho Jung, Shinjae Yoo, Jiook Cha, Taesup Moon:
SwiFT: Swin 4D fMRI Transformer. - Giannis Daras, Yuval Dagan, Alex Dimakis, Constantinos Daskalakis:
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent. - Qianqian Shen, Yunhan Zhao, Nahyun Kwon, Jeeeun Kim, Yanan Li, Shu Kong:
A High-Resolution Dataset for Instance Detection with Multi-View Object Capture. - Hirofumi Tsuruta, Hiroyuki Yamazaki, Ryota Maeda, Ryotaro Tamura, Jennifer N. Wei, Zelda E. Mariet, Poomarin Phloyphisut, Hidetoshi Shimokawa, Joseph R. Ledsam, Lucy J. Colwell, Akihiro Imura:
AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions. - Minsoo Kim, Sihwa Lee, Janghwan Lee, Sukjin Hong, Du-Seong Chang, Wonyong Sung, Jungwook Choi:
Token-Scaled Logit Distillation for Ternary Weight Generative Language Models. - Lenart Treven, Jonas Hübotter, Bhavya Sukhija, Florian Dörfler, Andreas Krause:
Efficient Exploration in Continuous-time Model-based Reinforcement Learning. - Hengrui Cai, Yixin Wang, Michael I. Jordan, Rui Song:
On Learning Necessary and Sufficient Causal Graphs. - Rok Roskar, Chandrasekhar Ramakrishnan, Michele Volpi, Fernando Pérez-Cruz, Lilian Gasser, Firat Ozdemir, Patrick Paitz, Mohammad Alisafaee, Philipp Fischer, Ralf Grubenmann, Eliza Harris, Tasko Olevski, Carl Remlinger, Luis Salamanca, Elisabet Capon Garcia, Lorenzo Cavazzi, Jakub Chrobasik, Darlin Cordoba Osnas, Alessandro Degano, Jimena Dupre, Wesley Johnson, Eike Kettner, Laura Kinkead, Sean D. Murphy, Flora Thiebaut, Olivier Verscheure:
Renku: a platform for sustainable data science. - Jian Meng, Li Yang, Kyungmin Lee, Jinwoo Shin, Deliang Fan, Jae-sun Seo:
Slimmed Asymmetrical Contrastive Learning and Cross Distillation for Lightweight Model Training. - Myong Chol Jung, He Zhao, Joanna Dipnall, Lan Du:
Beyond Unimodal: Generalising Neural Processes for Multimodal Uncertainty Estimation. - Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Thomas Rainforth, Arnaud Doucet:
Trans-Dimensional Generative Modeling via Jump Diffusion Models. - Chaofei Fan, Nick Hahn, Foram Kamdar, Donald T. Avansino, Guy H. Wilson, Leigh R. Hochberg, Krishna V. Shenoy, Jaimie M. Henderson, Francis R. Willett:
Plug-and-Play Stability for Intracortical Brain-Computer Interfaces: A One-Year Demonstration of Seamless Brain-to-Text Communication. - Ankit Vishnubhotla, Charlotte Loh, Akash Srivastava, Liam Paninski, Cole L. Hurwitz:
Towards robust and generalizable representations of extracellular data using contrastive learning. - Anh-Dung Dinh, Daochang Liu, Chang Xu:
Rethinking Conditional Diffusion Sampling with Progressive Guidance. - Brahma S. Pavse, Josiah Hanna:
State-Action Similarity-Based Representations for Off-Policy Evaluation. - Jinyang Li, Binyuan Hui, Ge Qu, Jiaxi Yang, Binhua Li, Bowen Li, Bailin Wang, Bowen Qin, Ruiying Geng, Nan Huo, Xuanhe Zhou, Chenhao Ma, Guoliang Li, Kevin Chen-Chuan Chang, Fei Huang, Reynold Cheng, Yongbin Li:
Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs. - Tong Xiang, Liangzhi Li, Wangyue Li, Mingbai Bai, Lu Wei, Bowen Wang, Noa Garcia:
CARE-MI: Chinese Benchmark for Misinformation Evaluation in Maternity and Infant Care. - Zhongbin Fang, Xiangtai Li, Xia Li, Joachim M. Buhmann, Chen Change Loy, Mengyuan Liu:
Explore In-Context Learning for 3D Point Cloud Understanding. - Xiaotong Luo, Yuan Xie, Yanyun Qu:
Learning Re-sampling Methods with Parameter Attribution for Image Super-resolution. - Manjie Xu, Guangyuan Jiang, Wei Liang, Chi Zhang, Yixin Zhu:
Interactive Visual Reasoning under Uncertainty. - Jaemoo Choi, Jaewoong Choi, Myungjoo Kang:
Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport. - Junqi Wang, Pei Wang, Patrick Shafto:
Generalized Belief Transport. - Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh:
Lie Point Symmetry and Physics-Informed Networks. - Tomer Galanti, Mengjia Xu, Liane Galanti, Tomaso A. Poggio:
Norm-based Generalization Bounds for Sparse Neural Networks. - Wenwen Zhang, Arvin Tashakori, Zenan Jiang, Amir Servati, Harishkumar Narayana, Saeid Soltanian, Rou Yi Yeap, Meng Han Ma, Lauren Toy, Peyman Servati:
Intelligent Knee Sleeves: A Real-time Multimodal Dataset for 3D Lower Body Motion Estimation Using Smart Textile. - Tal Amir, Steven J. Gortler, Ilai Avni, Ravina Ravina, Nadav Dym:
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem. - Jason Cheuk Nam Liang, Haihao Lu, Baoyu Zhou:
Online Ad Procurement in Non-stationary Autobidding Worlds. - David X. Wu, Anant Sahai:
Precise asymptotic generalization for multiclass classification with overparameterized linear models. - Michael A. Lepori, Thomas Serre, Ellie Pavlick:
Break It Down: Evidence for Structural Compositionality in Neural Networks. - Szymon Tworkowski, Konrad Staniszewski, Mikolaj Pacek, Yuhuai Wu, Henryk Michalewski, Piotr Milos:
Focused Transformer: Contrastive Training for Context Scaling. - Zeyinzi Jiang, Chaojie Mao, Ziyuan Huang, Ao Ma, Yiliang Lv, Yujun Shen, Deli Zhao, Jingren Zhou:
Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone. - Peiyu Yu, Yaxuan Zhu, Sirui Xie, Xiaojian Ma, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu:
Learning Energy-Based Prior Model with Diffusion-Amortized MCMC. - Viorica Patraucean, Lucas Smaira, Ankush Gupta, Adrià Recasens, Larisa Markeeva, Dylan Banarse, Skanda Koppula, Joseph Heyward, Mateusz Malinowski, Yi Yang, Carl Doersch, Tatiana Matejovicova, Yury Sulsky, Antoine Miech, Alexandre Fréchette, Hanna Klimczak, Raphael Koster, Junlin Zhang, Stephanie Winkler, Yusuf Aytar, Simon Osindero, Dima Damen, Andrew Zisserman, João Carreira:
Perception Test: A Diagnostic Benchmark for Multimodal Video Models. - Saptarshi Roy, Raymond K. W. Wong, Yang Ni:
Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data. - Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri, Chuan Guo:
Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning. - Ali Younis, Erik B. Sudderth:
Differentiable and Stable Long-Range Tracking of Multiple Posterior Modes. - Florian Stimberg, Ayan Chakrabarti, Chun-Ta Lu, Hussein Hazimeh, Otilia Stretcu, Wei Qiao, Yintao Liu, Merve Kaya, Cyrus Rashtchian, Ariel Fuxman, Mehmet Tek, Sven Gowal:
Benchmarking Robustness to Adversarial Image Obfuscations. - Jacob A. Zavatone-Veth, Cengiz Pehlevan:
Learning Curves for Deep Structured Gaussian Feature Models. - Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou, Molei Tao:
Mirror Diffusion Models for Constrained and Watermarked Generation. - Manuel Tran, Yashin Dicente Cid, Amal Lahiani, Fabian J. Theis, Tingying Peng, Eldad Klaiman:
Training Transitive and Commutative Multimodal Transformers with LoReTTa. - Sarp Aykent, Tian Xia:
SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning. - Zunzhi You, Daochang Liu, Bohyung Han, Chang Xu:
Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense. - Can Qin, Shu Zhang, Ning Yu, Yihao Feng, Xinyi Yang, Yingbo Zhou, Huan Wang, Juan Carlos Niebles, Caiming Xiong, Silvio Savarese, Stefano Ermon, Yun Fu, Ran Xu:
UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild. - Kai Hu, Andy Zou, Zifan Wang, Klas Leino, Matt Fredrikson:
Unlocking Deterministic Robustness Certification on ImageNet. - Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong:
Bayesian Optimisation of Functions on Graphs. - Mengxue Qu, Yu Wu, Wu Liu, Xiaodan Liang, Jingkuan Song, Yao Zhao, Yunchao Wei:
RIO: A Benchmark for Reasoning Intention-Oriented Objects in Open Environments. - Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill:
Supervised Pretraining Can Learn In-Context Reinforcement Learning. - Zhaoyang Hai, Liyuan Pan, Xiabi Liu, Zhengzheng Liu, Mirna Yunita:
L2T-DLN: Learning to Teach with Dynamic Loss Network. - Jie Ma, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Structured Federated Learning through Clustered Additive Modeling. - Ege Beyazit, Jonathan Kozaczuk, Bo Li, Vanessa Wallace, Bilal Fadlallah:
An Inductive Bias for Tabular Deep Learning. - Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu:
Fairness-guided Few-shot Prompting for Large Language Models. - Lin Yang, Junlong Lyu, Wenlong Lyu, Zhitang Chen:
Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs. - Eric Nguyen, Michael Poli, Marjan Faizi, Armin W. Thomas, Michael Wornow, Callum Birch-Sykes, Stefano Massaroli, Aman Patel, Clayton M. Rabideau, Yoshua Bengio, Stefano Ermon, Christopher Ré, Stephen Baccus:
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution. - Ajil Jalal, Justin Singh Kang, Ananya Uppal, Kannan Ramchandran, Eric Price:
Learning a 1-layer conditional generative model in total variation. - Xinyi Xu, Thanh Lam, Chuan Sheng Foo, Bryan Kian Hsiang Low:
Model Shapley: Equitable Model Valuation with Black-box Access. - Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Robust Concept Erasure via Kernelized Rate-Distortion Maximization. - Haotong Qin, Lei Ke, Xudong Ma, Martin Danelljan, Yu-Wing Tai, Chi-Keung Tang, Xianglong Liu, Fisher Yu:
BiMatting: Efficient Video Matting via Binarization. - Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin:
One Fits All: Power General Time Series Analysis by Pretrained LM. - Suyoung Lee, Myungsik Cho, Youngchul Sung:
Parameterizing Non-Parametric Meta-Reinforcement Learning Tasks via Subtask Decomposition. - Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas:
Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression. - Mingzhou Liu, Xinwei Sun, Lingjing Hu, Yizhou Wang:
Causal Discovery from Subsampled Time Series with Proxy Variables. - Shuang Li, Ke Li, Wei Li:
"Why Not Looking backward?" A Robust Two-Step Method to Automatically Terminate Bayesian Optimization. - Pan Lu, Baolin Peng, Hao Cheng, Michel Galley, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, Jianfeng Gao:
Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models. - Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, Jun Zhu:
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels. - Zuobai Zhang, Minghao Xu, Aurélie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang:
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction. - Don Kurian Dennis, Abhishek Shetty, Anish Prasad Sevekari, Kazuhito Koishida, Virginia Smith:
Progressive Ensemble Distillation: Building Ensembles for Efficient Inference. - Alexandr Andoni, Piotr Indyk, Sepideh Mahabadi, Shyam Narayanan:
Differentially Private Approximate Near Neighbor Counting in High Dimensions. - Dongjie Wang, Meng Xiao, Min Wu, Pengfei Wang, Yuanchun Zhou, Yanjie Fu:
Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions. - Kun Song, Huimin Ma, Bochao Zou, Huishuai Zhang, Weiran Huang:
FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning. - Zahra Gharaee, ZeMing Gong, Nicholas Pellegrino, Iuliia Zarubiieva, Joakim Bruslund Haurum, Scott C. Lowe, Jaclyn T. A. McKeown, Chris C. Y. Ho, Joschka McLeod, Yi-Yun C. Wei, Jireh Agda, Sujeevan Ratnasingham, Dirk Steinke, Angel X. Chang, Graham W. Taylor, Paul W. Fieguth:
A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset. - Wei Liu, Jun Wang, Haozhao Wang, Ruixuan Li, Zhiying Deng, Yuankai Zhang, Yang Qiu:
D-Separation for Causal Self-Explanation. - Christopher Solinas, Douglas Rebstock, Nathan R. Sturtevant, Michael Buro:
History Filtering in Imperfect Information Games: Algorithms and Complexity. - Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang:
Constant Approximation for Individual Preference Stable Clustering. - Gecia Bravo Hermsdorff, David S. Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva:
Intervention Generalization: A View from Factor Graph Models. - Yuheng Ma, Han Zhang, Yuchao Cai, Hanfang Yang:
Decision Tree for Locally Private Estimation with Public Data. - Haoran Ye, Jiarui Wang, Zhiguang Cao, Helan Liang, Yong Li:
DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization. - Zexu Sun, Bowei He, Jinxin Liu, Xu Chen, Chen Ma, Shuai Zhang:
Offline Imitation Learning with Variational Counterfactual Reasoning. - Haoyu Chen, Hao Tang, Radu Timofte, Luc Van Gool, Guoying Zhao:
LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer. - Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song:
Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data. - Xin Cheng, Di Luo, Xiuying Chen, Lemao Liu, Dongyan Zhao, Rui Yan:
Lift Yourself Up: Retrieval-augmented Text Generation with Self-Memory. - Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu:
Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge. - Chen-Hao Chao, Wei-Fang Sun, Yen-Chang Hsu, Zsolt Kira, Chun-Yi Lee:
Training Energy-Based Normalizing Flow with Score-Matching Objectives. - Jiawei Lin, Jiaqi Guo, Shizhao Sun, Zijiang Yang, Jian-Guang Lou, Dongmei Zhang:
LayoutPrompter: Awaken the Design Ability of Large Language Models. - Urte Adomaityte, Gabriele Sicuro, Pierpaolo Vivo:
Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach. - Andres Potapczynski, Marc Finzi, Geoff Pleiss, Andrew Gordon Wilson:
CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra. - Eghbal A. Hosseini, Evelina Fedorenko:
Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language. - Ibrahim El Shar, Daniel Jiang:
Weakly Coupled Deep Q-Networks. - Youbang Sun, Tao Liu, Ruida Zhou, P. R. Kumar, Shahin Shahrampour:
Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games. - Fabien Casenave, Brian Staber, Xavier Roynard:
MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability. - Siyuan Zhou, Yilun Du, Shun Zhang, Mengdi Xu, Yikang Shen, Wei Xiao, Dit-Yan Yeung, Chuang Gan:
Adaptive Online Replanning with Diffusion Models. - Zige Wang, Yonggang Zhang, Zhen Fang, Long Lan, Wenjing Yang, Bo Han:
SODA: Robust Training of Test-Time Data Adaptors. - Vincent Froese, Christoph Hertrich:
Training Neural Networks is NP-Hard in Fixed Dimension. - Yukang Yang, Dongnan Gui, Yuhui Yuan, Weicong Liang, Haisong Ding, Han Hu, Kai Chen:
GlyphControl: Glyph Conditional Control for Visual Text Generation. - Sungho Choi, Seungyul Han, Woojun Kim, Jongseong Chae, Whiyoung Jung, Youngchul Sung:
Domain Adaptive Imitation Learning with Visual Observation. - Usha Bhalla, Suraj Srinivas, Himabindu Lakkaraju:
Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability. - Neel Guha, Julian Nyarko, Daniel E. Ho, Christopher Ré, Adam Chilton, K. Aditya, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N. Rockmore, Diego Zambrano, Dmitry Talisman, Enam Hoque, Faiz Surani, Frank Fagan, Galit Sarfaty, Gregory M. Dickinson, Haggai Porat, Jason Hegland, Jessica Wu, Joe Nudell, Joel Niklaus, John J. Nay, Jonathan H. Choi, Kevin Tobia, Margaret Hagan, Megan Ma, Michael A. Livermore, Nikon Rasumov-Rahe, Nils Holzenberger, Noam Kolt, Peter Henderson, Sean Rehaag, Sharad Goel, Shang Gao, Spencer Williams, Sunny Gandhi, Tom Zur, Varun Iyer, Zehua Li:
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. - Rickard Karlsson, Jesse H. Krijthe:
Detecting hidden confounding in observational data using multiple environments. - Xuehao Ding, Dongsoo Lee, Joshua Melander, George Sivulka, Surya Ganguli, Stephen Baccus:
Information Geometry of the Retinal Representation Manifold. - Vikash Kumar, Rutav M. Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Abhishek Gupta, Aravind Rajeswaran:
RoboHive: A Unified Framework for Robot Learning. - Mufeng Tang, Helen Barron, Rafal Bogacz:
Sequential Memory with Temporal Predictive Coding. - Alexis Bellot, Alan Malek, Silvia Chiappa:
Transportability for Bandits with Data from Different Environments. - Matthew Jagielski, Milad Nasr, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini, Florian Tramèr:
Students Parrot Their Teachers: Membership Inference on Model Distillation. - Tsun-Hsuan Johnson Wang, Juntian Zheng, Pingchuan Ma, Yilun Du, Byungchul Kim, Andrew Spielberg, Joshua B. Tenenbaum, Chuang Gan, Daniela Rus:
DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models. - Jimmy Z. Di, Jack Douglas, Jayadev Acharya, Gautam Kamath, Ayush Sekhari:
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks. - Shengran Hu, Jeff Clune:
Thought Cloning: Learning to Think while Acting by Imitating Human Thinking. - Hugues Van Assel, Titouan Vayer, Rémi Flamary, Nicolas Courty:
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities. - Nurendra Choudhary, Nikhil Rao, Chandan K. Reddy:
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach. - Shiqi Chen, Yiran Zhao, Jinghan Zhang, I-Chun Chern, Siyang Gao, Pengfei Liu, Junxian He:
FELM: Benchmarking Factuality Evaluation of Large Language Models. - Adam B. Cobb, Anirban Roy, Daniel Elenius, F. Michael Heim, Brian Swenson, Sydney Whittington, James D. Walker, Theodore Bapty, Joseph Hite, Karthik Ramani, Christopher McComb, Susmit Jha:
AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs. - Xiaohui Chen, Yinkai Wang, Yuanqi Du, Soha Hassoun, Liping Liu:
On Separate Normalization in Self-supervised Transformers. - Qiang Zhou, Weize Li, Lihan Jiang, Guoliang Wang, Guyue Zhou, Shanghang Zhang, Hao Zhao:
PAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection. - Ilze Amanda Auzina, Çagatay Yildiz, Sara Magliacane, Matthias Bethge, Efstratios Gavves:
Modulated Neural ODEs. - Bowen Gao, Bo Qiang, Haichuan Tan, Yinjun Jia, Minsi Ren, Minsi Lu, Jingjing Liu, Wei-Ying Ma, Yanyan Lan:
DrugCLIP: Contrasive Protein-Molecule Representation Learning for Virtual Screening. - Kyurae Kim, Jisu Oh, Kaiwen Wu, Yi-An Ma, Jacob R. Gardner:
On the Convergence of Black-Box Variational Inference. - Siran Dai, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang:
DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework. - Tianyu Chen, Kevin Bello, Bryon Aragam, Pradeep Ravikumar:
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models. - Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas:
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. - Xudong Xu, Dejan Markovic, Jacob Sandakly, Todd Keebler, Steven Krenn, Alexander Richard:
Sounding Bodies: Modeling 3D Spatial Sound of Humans Using Body Pose and Audio. - Noah Hollmann, Samuel Müller, Frank Hutter:
Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering. - Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, Peter Stone:
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning. - Amira Abbas, Robbie King, Hsin-Yuan Huang, William J. Huggins, Ramis Movassagh, Dar Gilboa, Jarrod R. McClean:
On quantum backpropagation, information reuse, and cheating measurement collapse. - Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander V. Gasnikov, Alexey Naumov, Eric Moulines:
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities. - Marina Knittel, Max Springer, John P. Dickerson, MohammadTaghi Hajiaghayi:
Fair, Polylog-Approximate Low-Cost Hierarchical Clustering. - Chenhang Cui, Yazhou Ren, Jingyu Pu, Jiawei Li, Xiaorong Pu, Tianyi Wu, Yutao Shi, Lifang He:
A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective. - Minghua Liu, Ruoxi Shi, Kaiming Kuang, Yinhao Zhu, Xuanlin Li, Shizhong Han, Hong Cai, Fatih Porikli, Hao Su:
OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding. - Kesen Zhao, Shuchang Liu, Qingpeng Cai, Xiangyu Zhao, Ziru Liu, Dong Zheng, Peng Jiang, Kun Gai:
KuaiSim: A Comprehensive Simulator for Recommender Systems. - Shiqiang Zhang, Juan S. Campos, Christian Feldmann, David Walz, Frederik Sandfort, Miriam Mathea, Calvin Tsay, Ruth Misener:
Optimizing over trained GNNs via symmetry breaking. - Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
REx: Data-Free Residual Quantization Error Expansion. - Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer:
A Unified, Scalable Framework for Neural Population Decoding. - Wei He, Kai Han, Ying Nie, Chengcheng Wang, Yunhe Wang:
Species196: A One-Million Semi-supervised Dataset for Fine-grained Species Recognition. - Liya Hu, Zhiang Dong, Jingyuan Chen, Guifeng Wang, Zhihua Wang, Zhou Zhao, Fei Wu:
PTADisc: A Cross-Course Dataset Supporting Personalized Learning in Cold-Start Scenarios. - Zhuofan Ying, Peter Hase, Mohit Bansal:
Adaptive Contextual Perception: How To Generalize To New Backgrounds and Ambiguous Objects. - Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos:
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. - Xinran Xie, Man-Jie Yuan, Xuetong Bai, Wei Gao, Zhi-Hua Zhou:
On the Gini-impurity Preservation For Privacy Random Forests. - Walter Gerych, Kevin Hickey, Luke Buquicchio, Kavin Chandrasekaran, Abdulaziz Alajaji, Elke A. Rundensteiner, Emmanuel Agu:
Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes. - Hamish Flynn, David Reeb, Melih Kandemir, Jan R. Peters:
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures. - Shengjie Zhu, Abhinav Kumar, Masa Hu, Xiaoming Liu:
Tame a Wild Camera: In-the-Wild Monocular Camera Calibration. - Zhitong Gao, Shipeng Yan, Xuming He:
ATTA: Anomaly-aware Test-Time Adaptation for Out-of-Distribution Detection in Segmentation. - Xin Cheng, Yuzhou Cao, Haobo Wang, Hongxin Wei, Bo An, Lei Feng:
Regression with Cost-based Rejection. - Ted Moskovitz, Samo Hromadka, Ahmed Touati, Diana Borsa, Maneesh Sahani:
A State Representation for Diminishing Rewards. - Shaolei Zhang, Yang Feng:
Unified Segment-to-Segment Framework for Simultaneous Sequence Generation. - Salva Rühling Cachay, Bo Zhao, Hailey Joren, Rose Yu:
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting. - Yunsheng Bai, Atefeh Sohrabizadeh, Zongyue Qin, Ziniu Hu, Yizhou Sun, Jason Cong:
Towards a Comprehensive Benchmark for High-Level Synthesis Targeted to FPGAs. - Tobias Schröder, Zijing Ou, Jen Lim, Yingzhen Li, Sebastian J. Vollmer, Andrew Duncan:
Energy Discrepancies: A Score-Independent Loss for Energy-Based Models. - Tinglin Huang, Ziniu Hu, Rex Ying:
Learning to Group Auxiliary Datasets for Molecule. - Liming Wu, Zhichao Hou, Jirui Yuan, Yu Rong, Wenbing Huang:
Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics. - Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Özgür, Olgica Milenkovic:
Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection. - Stephen McAleer, Gabriele Farina, Gaoyue Zhou, Mingzhi Wang, Yaodong Yang, Tuomas Sandholm:
Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning. - Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar:
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing. - Kyle Hsu, William Dorrell, James C. R. Whittington, Jiajun Wu, Chelsea Finn:
Disentanglement via Latent Quantization. - Oscar Li, James Harrison, Jascha Sohl-Dickstein, Virginia Smith, Luke Metz:
Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies. - Tongxin Li, Yiheng Lin, Shaolei Ren, Adam Wierman:
Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions. - Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi:
Graph Contrastive Learning with Stable and Scalable Spectral Encoding. - Junyi Zhang, Charles Herrmann, Junhwa Hur, Luisa Polania Cabrera, Varun Jampani, Deqing Sun, Ming-Hsuan Yang:
A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence. - Xi Ye, Qiaochu Chen, Isil Dillig, Greg Durrett:
SatLM: Satisfiability-Aided Language Models Using Declarative Prompting. - Sergey Shuvaev, Evgeny Amelchenko, Dmitry A. Smagin, Natalia N. Kudryavtseva, Grigori Enikolopov, Alexei A. Koulakov:
A normative theory of social conflict. - Donglin Xia, Xiao Wang, Nian Liu, Chuan Shi:
Learning Invariant Representations of Graph Neural Networks via Cluster Generalization. - Kwangjun Ahn, Xiang Cheng, Hadi Daneshmand, Suvrit Sra:
Transformers learn to implement preconditioned gradient descent for in-context learning. - Junyu Huang, Qilong Feng, Ziyun Huang, Jinhui Xu, Jianxin Wang:
Linear Time Algorithms for k-means with Multi-Swap Local Search. - Sebastian Salazar:
VaRT: Variational Regression Trees. - Ramy Mounir, Sujal Vijayaraghavan, Sudeep Sarkar:
STREAMER: Streaming Representation Learning and Event Segmentation in a Hierarchical Manner. - Sotetsu Koyamada, Shinri Okano, Soichiro Nishimori, Yu Murata, Keigo Habara, Haruka Kita, Shin Ishii:
Pgx: Hardware-Accelerated Parallel Game Simulators for Reinforcement Learning. - Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk:
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity. - Zixuan Jiang, Jiaqi Gu, Hanqing Zhu, David Z. Pan:
Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers. - Emma Chen, Aman Kansal, Julie Chen, Boyang Tom Jin, Julia Rachel Reisler, David A. Kim, Pranav Rajpurkar:
Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine. - Yun Yue, Zhiling Ye, Jiadi Jiang, Yongchao Liu, Ke Zhang:
AGD: an Auto-switchable Optimizer using Stepwise Gradient Difference for Preconditioning Matrix. - Minsik Cho, Saurabh Adya, Devang Naik:
PDP: Parameter-free Differentiable Pruning is All You Need. - Tung Nguyen, Sudhanshu Agrawal, Aditya Grover:
ExPT: Synthetic Pretraining for Few-Shot Experimental Design. - Shibo Hao, Tianyang Liu, Zhen Wang, Zhiting Hu:
ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings. - Yunyao Mao, Jiajun Deng, Wengang Zhou, Li Li, Yao Fang, Houqiang Li:
CLIP4HOI: Towards Adapting CLIP for Practical Zero-Shot HOI Detection. - Parshin Shojaee, Kazem Meidani, Amir Barati Farimani, Chandan K. Reddy:
Transformer-based Planning for Symbolic Regression. - Sriram Balasubramanian, Gaurang Sriramanan, Vinu Sankar Sadasivan, Soheil Feizi:
Exploring Geometry of Blind Spots in Vision models. - Omar Chehab, Aapo Hyvärinen, Andrej Risteski:
Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond. - Lauren E. Conger, Franca Hoffmann, Eric Mazumdar, Lillian J. Ratliff:
Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flows. - Lu Mi, Trung Le, Tianxing He, Eli Shlizerman, Uygar Sümbül:
Learning Time-Invariant Representations for Individual Neurons from Population Dynamics. - Hyeonsu Kim, Jeheon Woo, Seonghwan Kim, Seokhyun Moon, Jun Hyeong Kim, Woo Youn Kim:
GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising. - Hao Yang, Haiyang Wang, Di Dai, Liwei Wang:
PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds. - Samuel Holt, Alihan Hüyük, Mihaela van der Schaar:
Active Observing in Continuous-time Control. - Pieter-Jan Hoedt, Günter Klambauer:
Principled Weight Initialisation for Input-Convex Neural Networks. - Yifan Zang, Jinmin He, Kai Li, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng:
Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning. - Khaled Eldowa, Emmanuel Esposito, Tommaso Cesari, Nicolò Cesa-Bianchi:
On the Minimax Regret for Online Learning with Feedback Graphs. - Haochen Wang, Junsong Fan, Yuxi Wang, Kaiyou Song, Tong Wang, Zhaoxiang Zhang:
DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions. - Hadi Vafaii, Jacob L. Yates, Daniel Butts:
Hierarchical VAEs provide a normative account of motion processing in the primate brain. - Xinran Zhu, Kaiwen Wu, Natalie Maus, Jacob R. Gardner, David Bindel:
Variational Gaussian Processes with Decoupled Conditionals. - Karttikeya Mangalam, Raiymbek Akshulakov, Jitendra Malik:
EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language Understanding. - Manbir Gulati, Paul F. Roysdon:
TabMT: Generating tabular data with masked transformers. - Gabriel Sarch, Michael J. Tarr, Katerina Fragkiadaki, Leila Wehbe:
Brain Dissection: fMRI-trained Networks Reveal Spatial Selectivity in the Processing of Natural Images. - Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl:
Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models. - Yingjun Du, Zehao Xiao, Shengcai Liao, Cees Snoek:
ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion. - Cong Lu, Philip J. Ball, Yee Whye Teh, Jack Parker-Holder:
Synthetic Experience Replay. - Weiwei Sun, Lingyong Yan, Zheng Chen, Shuaiqiang Wang, Haichao Zhu, Pengjie Ren, Zhumin Chen, Dawei Yin, Maarten de Rijke, Zhaochun Ren:
Learning to Tokenize for Generative Retrieval. - Yunchang Yang, Han Zhong, Tianhao Wu, Bin Liu, Liwei Wang, Simon S. Du:
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback. - Minshuo Chen, Yu Bai, H. Vincent Poor, Mengdi Wang:
Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations. - Zheyun Qin, Cheng Han, Qifan Wang, Xiushan Nie, Yilong Yin, Xiankai Lu:
Unified 3D Segmenter As Prototypical Classifiers. - Arijit Ray, Filip Radenovic, Abhimanyu Dubey, Bryan A. Plummer, Ranjay Krishna, Kate Saenko:
Cola: A Benchmark for Compositional Text-to-image Retrieval. - Yonghan Jung, Ivan Diaz, Jin Tian, Elias Bareinboim:
Estimating Causal Effects Identifiable from a Combination of Observations and Experiments. - Haoxuan Qu, Xiaofei Hui, Yujun Cai, Jun Liu:
LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition. - Dishank Bansal, Ricky T. Q. Chen, Mustafa Mukadam, Brandon Amos:
TaskMet: Task-driven Metric Learning for Model Learning. - Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh, Kristin P. Bennett:
Pairwise Causality Guided Transformers for Event Sequences. - Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark:
Self-Refine: Iterative Refinement with Self-Feedback. - Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica:
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. - Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan A. Rossi, Murat Kocaoglu:
Causal Discovery in Semi-Stationary Time Series. - Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris:
Fine-grained Expressivity of Graph Neural Networks. - Yangruibo Ding, Zijian Wang, Wasi Uddin Ahmad, Hantian Ding, Ming Tan, Nihal Jain, Murali Krishna Ramanathan, Ramesh Nallapati, Parminder Bhatia, Dan Roth, Bing Xiang:
CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion. - Yangru Huang, Peixi Peng, Yifan Zhao, Haoran Xu, Mengyue Geng, Yonghong Tian:
Hierarchical Adaptive Value Estimation for Multi-modal Visual Reinforcement Learning. - Evgenii Chzhen, Christophe Giraud, Zhen Li, Gilles Stoltz:
Small Total-Cost Constraints in Contextual Bandits with Knapsacks, with Application to Fairness. - Pengyun Zhu, Long Wen, Jinfei Liu, Feng Xue, Jian Lou, Zhibo Wang, Kui Ren:
CAPP-130: A Corpus of Chinese Application Privacy Policy Summarization and Interpretation. - Samuel Lanthaler, T. Konstantin Rusch, Siddhartha Mishra:
Neural Oscillators are Universal. - Apoorva Sharma, Sushant Veer, Asher Hancock, Heng Yang, Marco Pavone, Anirudha Majumdar:
PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction. - Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer:
Image Captioners Are Scalable Vision Learners Too. - Hengli Li, Song-Chun Zhu, Zilong Zheng:
Diplomat: A Dialogue Dataset for Situated PragMATic Reasoning. - Qihe Huang, Lei Shen, Ruixin Zhang, Shouhong Ding, Binwu Wang, Zhengyang Zhou, Yang Wang:
CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement. - Anqi Mao, Mehryar Mohri, Yutao Zhong:
Structured Prediction with Stronger Consistency Guarantees. - Zhengfei Kuang, Yunzhi Zhang, Hong-Xing Yu, Samir Agarwala, Shangzhe Wu, Jiajun Wu:
Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark. - Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro:
Explainable Brain Age Prediction using coVariance Neural Networks. - Ambar Pal, Jeremias Sulam, René Vidal:
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness. - Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob N. Foerster, Satinder Singh, Feryal M. P. Behbahani:
Structured State Space Models for In-Context Reinforcement Learning. - Maksym Andriushchenko, Dara Bahri, Hossein Mobahi, Nicolas Flammarion:
Sharpness-Aware Minimization Leads to Low-Rank Features. - Abdulkadir Canatar, Jenelle Feather, Albert J. Wakhloo, SueYeon Chung:
A Spectral Theory of Neural Prediction and Alignment. - Shenzhi Wang, Qisen Yang, Jiawei Gao, Matthieu Gaetan Lin, Hao Chen, Liwei Wu, Ning Jia, Shiji Song, Gao Huang:
Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning. - Yifei Zhou, Juntao Ren, Fengyu Li, Ramin Zabih, Ser Nam Lim:
Test-Time Distribution Normalization for Contrastively Learned Visual-language Models. - Shankar Padmanabhan, Yasumasa Onoe, Michael J. Q. Zhang, Greg Durrett, Eunsol Choi:
Propagating Knowledge Updates to LMs Through Distillation. - Yuqi Chen, Kan Ren, Yansen Wang, Yuchen Fang, Weiwei Sun, Dongsheng Li:
ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling. - Thomas M. Sutter, Alain Ryser, Joram Liebeskind, Julia E. Vogt:
Differentiable Random Partition Models. - Chenwei Wu, Holden Lee, Rong Ge:
Connecting Pre-trained Language Model and Downstream Task via Properties of Representation. - Xueting Li, Shalini De Mello, Sifei Liu, Koki Nagano, Umar Iqbal, Jan Kautz:
Generalizable One-shot 3D Neural Head Avatar. - Owen Howell, David Klee, Ondrej Biza, Linfeng Zhao, Robin Walters:
Equivariant Single View Pose Prediction Via Induced and Restriction Representations. - Yimeng Min, Yiwei Bai, Carla P. Gomes:
Unsupervised Learning for Solving the Travelling Salesman Problem. - Wei Xing, Yuxin Wang, Zheng Xing:
ContinuAR: Continuous Autoregression For Infinite-Fidelity Fusion. - Shengzhong Liu, Tomoyoshi Kimura, Dongxin Liu, Ruijie Wang, Jinyang Li, Suhas N. Diggavi, Mani B. Srivastava, Tarek F. Abdelzaher:
FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space. - Francesco Montagna, Atalanti-Anastasia Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco, Dominik Janzing, Bryon Aragam, Francesco Locatello:
Assumption violations in causal discovery and the robustness of score matching. - Chen Xu, Xiuyuan Cheng, Yao Xie:
Normalizing flow neural networks by JKO scheme. - Taira Tsuchiya, Shinji Ito, Junya Honda:
Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds. - Ning Liu, Siavash Jafarzadeh, Yue Yu:
Domain Agnostic Fourier Neural Operators. - Adel Nabli, Eugene Belilovsky, Edouard Oyallon:
A2CiD2: Accelerating Asynchronous Communication in Decentralized Deep Learning. - Qinsi Wang, Jinghan Ke, Zhi Liang, Sihai Zhang:
MathNAS: If Blocks Have a Role in Mathematical Architecture Design. - Chengchang Liu, Cheng Chen, Luo Luo, John C. S. Lui:
Block Broyden's Methods for Solving Nonlinear Equations. - Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, Trevor Darrell:
Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence. - Zixing Song, Yifei Zhang, Irwin King:
No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning. - Arlind Kadra, Maciej Janowski, Martin Wistuba, Josif Grabocka:
Scaling Laws for Hyperparameter Optimization. - Ruozi Huang, Xipeng Wu, Hongsheng Yu, Zhong Fan, Haobo Fu, Qiang Fu, Wei Yang:
A Robust and Opponent-Aware League Training Method for StarCraft II. - Drago Plecko, Elias Bareinboim:
Causal Fairness for Outcome Control. - Federico Danieli, Miguel Sarabia, Xavier Suau Cuadros, Pau Rodríguez, Luca Zappella:
DeepPCR: Parallelizing Sequential Operations in Neural Networks. - Lin Wang, Yongxin Guo, Tao Lin, Xiaoying Tang:
DELTA: Diverse Client Sampling for Fasting Federated Learning. - Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi Rui Tam, Keith Stevens, Abdullah Barhoum, Duc Nguyen, Oliver Stanley, Richárd Nagyfi, Shahul ES, Sameer Suri, David Glushkov, Arnav Dantuluri, Andrew Maguire, Christoph Schuhmann, Huu Nguyen, Alexander Mattick:
OpenAssistant Conversations - Democratizing Large Language Model Alignment. - Ahmed M. Alaa, Zaid Ahmad, Mark J. van der Laan:
Conformal Meta-learners for Predictive Inference of Individual Treatment Effects. - Jade Copet, Felix Kreuk, Itai Gat, Tal Remez, David Kant, Gabriel Synnaeve, Yossi Adi, Alexandre Défossez:
Simple and Controllable Music Generation. - Wenxiao Wang, Soheil Feizi:
Temporal Robustness against Data poisoning. - Tao Shen, Yifan Cui:
Optimal Treatment Regimes for Proximal Causal Learning. - Zhong Yi Wan, Ricardo Baptista, Anudhyan Boral, Yi-Fan Chen, John Anderson, Fei Sha, Leonardo Zepeda-Núñez:
Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models. - Yuankai Luo, Veronika Thost, Lei Shi:
Transformers over Directed Acyclic Graphs. - Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Understanding and Mitigating Copying in Diffusion Models. - Radu Marinescu, Debarun Bhattacharjya, Junkyu Lee, Fábio Gagliardi Cozman, Alexander G. Gray:
Credal Marginal MAP. - Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert D. Nowak:
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits. - Ashok Cutkosky, Aaron Defazio, Harsh Mehta:
Mechanic: A Learning Rate Tuner. - Dorde Zikelic, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, Thomas A. Henzinger:
Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees. - Vivek Bharadwaj, Osman Asif Malik, Riley Murray, Laura Grigori, Aydin Buluç, James Demmel:
Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition. - Zihan Zhu, Ethan Fang, Zhuoran Yang:
Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games. - Jiakang Yuan, Bo Zhang, Xiangchao Yan, Botian Shi, Tao Chen, Yikang Li, Yu Qiao:
AD-PT: Autonomous Driving Pre-Training with Large-scale Point Cloud Dataset. - Tom Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi:
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors. - Ignavier Ng, Yujia Zheng, Xinshuai Dong, Kun Zhang:
On the Identifiability of Sparse ICA without Assuming Non-Gaussianity. - Yutong He, Xinmeng Huang, Kun Yuan:
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much? - Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang:
Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck. - Maria-Florina Balcan, Steve Hanneke, Rattana Pukdee, Dravyansh Sharma:
Reliable learning in challenging environments. - Long-Kai Huang, Peilin Zhao, Junzhou Huang, Sinno Jialin Pan:
Retaining Beneficial Information from Detrimental Data for Neural Network Repair. - Lujie Xia, Ziluo Ding, Rui Zhao, Jiyuan Zhang, Lei Ma, Zhaofei Yu, Tiejun Huang, Ruiqin Xiong:
Unsupervised Optical Flow Estimation with Dynamic Timing Representation for Spike Camera. - Abhishek Sinha, Ativ Joshi, Rajarshi Bhattacharjee, Cameron Musco, Mohammad Hajiesmaili:
No-regret Algorithms for Fair Resource Allocation. - Josh Alman, Jiehao Liang, Zhao Song, Ruizhe Zhang, Danyang Zhuo:
Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing. - Xihan Li, Xiang Chen, Rasul Tutunov, Haitham Bou-Ammar, Lei Wang, Jun Wang:
Online PCA in Converging Self-consistent Field Equations. - Yangtian Zhang, Zuobai Zhang, Bozitao Zhong, Sanchit Misra, Jian Tang:
DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing. - Chun-Han Yao, Amit Raj, Wei-Chih Hung, Michael Rubinstein, Yuanzhen Li, Ming-Hsuan Yang, Varun Jampani:
ARTIC3D: Learning Robust Articulated 3D Shapes from Noisy Web Image Collections. - Chi Gao, Zidong Zhou, Luping Shi:
Noether Embedding: Efficient Learning of Temporal Regularities. - Ruijie Zheng, Xiyao Wang, Yanchao Sun, Shuang Ma, Jieyu Zhao, Huazhe Xu, Hal Daumé III, Furong Huang:
TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning. - Sadaf Salehkalaibar, Buu Phan, Jun Chen, Wei Yu, Ashish Khisti:
On the choice of Perception Loss Function for Learned Video Compression. - Xin-Qiang Cai, Yu-Jie Zhang, Chao-Kai Chiang, Masashi Sugiyama:
Imitation Learning from Vague Feedback. - Yuchen Bai, Jean-Baptiste Durand, Grégoire Vincent, Florence Forbes:
Semantic segmentation of sparse irregular point clouds for leaf/wood discrimination. - Davoud Ataee Tarzanagh, Yingcong Li, Xuechen Zhang, Samet Oymak:
Max-Margin Token Selection in Attention Mechanism. - Doyup Lee, Chiheon Kim, Minsu Cho, Wook-Shin Han:
Locality-Aware Generalizable Implicit Neural Representation. - Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, Dilip Krishnan:
StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners. - Niv Giladi, Shahar Gottlieb, Moran Shkolnik, Asaf Karnieli, Ron Banner, Elad Hoffer, Kfir Y. Levy, Daniel Soudry:
DropCompute: simple and more robust distributed synchronous training via compute variance reduction. - Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang:
A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning. - Gregory Dexter, Petros Drineas, David P. Woodruff, Taisuke Yasuda:
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming. - Binhui Xie, Shuang Li, Qingju Guo, Chi Harold Liu, Xinjing Cheng:
Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation. - Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell Nadal, Felix Heide, Michael Moeller:
Kissing to Find a Match: Efficient Low-Rank Permutation Representation. - Joshua B. Evans, Özgür Simsek:
Creating Multi-Level Skill Hierarchies in Reinforcement Learning. - Nathan Grinsztajn, Daniel Furelos-Blanco, Shikha Surana, Clément Bonnet, Tom Barrett:
Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization. - Yuzheng Hu, Ruicheng Xian, Qilong Wu, Qiuling Fan, Lang Yin, Han Zhao:
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective. - Adam Block, Ali Jadbabaie, Daniel Pfrommer, Max Simchowitz, Russ Tedrake:
Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior. - Samuel Goldman, John Bradshaw, Jiayi Xin, Connor W. Coley:
Prefix-Tree Decoding for Predicting Mass Spectra from Molecules. - Minki Kang, Seanie Lee, Jinheon Baek, Kenji Kawaguchi, Sung Ju Hwang:
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks. - Julius von Kügelgen, Michel Besserve, Wendong Liang, Luigi Gresele, Armin Kekic, Elias Bareinboim, David M. Blei, Bernhard Schölkopf:
Nonparametric Identifiability of Causal Representations from Unknown Interventions. - Yuxin Guo, Shijie Ma, Hu Su, Zhiqing Wang, Yuhao Zhao, Wei Zou, Siyang Sun, Yun Zheng:
Dual Mean-Teacher: An Unbiased Semi-Supervised Framework for Audio-Visual Source Localization. - Yizhou Zhang, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Liang Tong, Haifeng Chen, Yan Liu:
Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning. - Junhyuk So, Jungwon Lee, Daehyun Ahn, Hyungjun Kim, Eunhyeok Park:
Temporal Dynamic Quantization for Diffusion Models. - Xuanjie Liu, Daniel Chin, Yichen Huang, Gus Xia:
Learning Interpretable Low-dimensional Representation via Physical Symmetry. - Yasheng Sun, Yifan Yang, Houwen Peng, Yifei Shen, Yuqing Yang, Han Hu, Lili Qiu, Hideki Koike:
ImageBrush: Learning Visual In-Context Instructions for Exemplar-Based Image Manipulation. - Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Meek Separators and Their Applications in Targeted Causal Discovery. - Bong Gyun Kang, HyunGi Kim, Dahuin Jung, Sungroh Yoon:
CLeAR: Continual Learning on Algorithmic Reasoning for Human-like Intelligence. - Jheng-Wei Su, Kuei-Yu Tung, Chi-Han Peng, Peter Wonka, Hung-Kuo Chu:
SLIBO-Net: Floorplan Reconstruction via Slicing Box Representation with Local Geometry Regularization. - Hoki Kim, Jinseong Park, Yujin Choi, Jaewook Lee:
Fantastic Robustness Measures: The Secrets of Robust Generalization. - Ilias Diakonikolas, Daniel Kane, Jasper C. H. Lee, Ankit Pensia, Thanasis Pittas:
A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm. - Simian Luo, Chuanhao Yan, Chenxu Hu, Hang Zhao:
Diff-Foley: Synchronized Video-to-Audio Synthesis with Latent Diffusion Models. - David Recasens, Martin R. Oswald, Marc Pollefeys, Javier Civera:
The Drunkard's Odometry: Estimating Camera Motion in Deforming Scenes. - Ting Li, Chengchun Shi, Jianing Wang, Fan Zhou, Hongtu Zhu:
Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making. - Seunghun Lee, Jaewon Chu, Sihyeon Kim, Juyeon Ko, Hyunwoo J. Kim:
Advancing Bayesian Optimization via Learning Correlated Latent Space. - Pierre Marion:
Generalization bounds for neural ordinary differential equations and deep residual networks. - Sai Aparna Aketi, Abolfazl Hashemi, Kaushik Roy:
Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data. - Thomas Paniagua, Ryan Grainger, Tianfu Wu:
QuadAttacK: A Quadratic Programming Approach to Learning Ordered Top-K Adversarial Attacks. - Shiwei Liu, Tian Zhu, Milong Ren, Chungong Yu, Dongbo Bu, Haicang Zhang:
Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model. - Jihui Jin, Etienne Ollivier, Richard Touret, Matthew McKinley, Karim Sabra, Justin Romberg:
PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems. - Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, Ronan Le Bras, Akari Asai, Xinyan Yu, Dragomir Radev, Noah A. Smith, Yejin Choi, Kentaro Inui:
RealTime QA: What's the Answer Right Now? - Dan Friedman, Alexander Wettig, Danqi Chen:
Learning Transformer Programs. - Xianhang Li, Zeyu Wang, Cihang Xie:
An Inverse Scaling Law for CLIP Training. - Minyoung Hwang, Gunmin Lee, Hogun Kee, Chan Woo Kim, Kyungjae Lee, Songhwai Oh:
Sequential Preference Ranking for Efficient Reinforcement Learning from Human Feedback. - Cheng-Ju Ho, Chen-Hsuan Tai, Yen-Yu Lin, Ming-Hsuan Yang, Yi-Hsuan Tsai:
Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection. - Jiashuo Wang, Haozhao Wang, Shichao Sun, Wenjie Li:
Aligning Language Models with Human Preferences via a Bayesian Approach. - Joel Daniel Andersson, Rasmus Pagh:
A Smooth Binary Mechanism for Efficient Private Continual Observation. - Haocheng Xi, Changhao Li, Jianfei Chen, Jun Zhu:
Training Transformers with 4-bit Integers. - Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor:
TD Convergence: An Optimization Perspective. - Zekun Li, Shiyang Li, Xifeng Yan:
Time Series as Images: Vision Transformer for Irregularly Sampled Time Series. - Xiangning Chen, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Hieu Pham, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V. Le:
Symbolic Discovery of Optimization Algorithms. - Tianyu Pang, Cheng Lu, Chao Du, Min Lin, Shuicheng Yan, Zhijie Deng:
On Calibrating Diffusion Probabilistic Models. - Wenliang Dai, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, Steven C. H. Hoi:
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning. - Thomas Steinke, Milad Nasr, Matthew Jagielski:
Privacy Auditing with One (1) Training Run. - Clément Bénard, Brian Staber, Sébastien Da Veiga:
Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization. - Wenqiang Wang, Chongyang Du, Tao Wang, Kaihao Zhang, Wenhan Luo, Lin Ma, Wei Liu, Xiaochun Cao:
Punctuation-level Attack: Single-shot and Single Punctuation Can Fool Text Models. - Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Weihong Luo, Liang Chen, Xiuqiang He, Xue (Steve) Liu:
Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network. - Yicheng Li, Haobo Zhang, Qian Lin:
On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay. - Yiding Chen, Jerry Zhu, Kirthevasan Kandasamy:
Mechanism Design for Collaborative Normal Mean Estimation. - Kaipeng Zheng, Huishuai Zhang, Weiran Huang:
DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation. - Junpei Komiyama, Masaaki Imaizumi:
High-dimensional Contextual Bandit Problem without Sparsity. - Antoine Yang, Arsha Nagrani, Ivan Laptev, Josef Sivic, Cordelia Schmid:
VidChapters-7M: Video Chapters at Scale. - Sangwoong Yoon, Young-Uk Jin, Yung-Kyun Noh, Frank C. Park:
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach. - Sihui Dai, Wenxin Ding, Arjun Nitin Bhagoji, Daniel Cullina, Heather Zheng, Ben Zhao, Prateek Mittal:
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker. - Hezhe Qiao, Guansong Pang:
Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection. - Ziqiao Wang, Yongyi Mao:
Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds. - Li Yang, Chunfeng Yuan, Ziqi Zhang, Zhongang Qi, Yan Xu, Wei Liu, Ying Shan, Bing Li, Weiping Yang, Peng Li, Yan Wang, Weiming Hu:
Exploiting Contextual Objects and Relations for 3D Visual Grounding. - Yining Ma, Zhiguang Cao, Yeow Meng Chee:
Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt. - Hanlin Zhu, Paria Rashidinejad, Jiantao Jiao:
Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning. - Longlin Yu, Tianyu Xie, Yu Zhu, Tong Yang, Xiangyu Zhang, Cheng Zhang:
Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration. - Nicholas Roberts, Xintong Li, Dyah Adila, Sonia Cromp, Tzu-Heng Huang, Jitian Zhao, Frederic Sala:
Geometry-Aware Adaptation for Pretrained Models. - Keqiang Sun, Junting Pan, Yuying Ge, Hao Li, Haodong Duan, Xiaoshi Wu, Renrui Zhang, Aojun Zhou, Zipeng Qin, Yi Wang, Jifeng Dai, Yu Qiao, Limin Wang, Hongsheng Li:
JourneyDB: A Benchmark for Generative Image Understanding. - Akifumi Imanishi, Zijian Xu, Masayuki Takagi, Sixue Wang, Emilio Castillo:
A fast heuristic to optimize time-space tradeoff for large models. - Yi Zhang, Xiaoyu Shi, Dasong Li, Xiaogang Wang, Jian Wang, Hongsheng Li:
A Unified Conditional Framework for Diffusion-based Image Restoration. - Haonan Yuan, Qingyun Sun, Xingcheng Fu, Ziwei Zhang, Cheng Ji, Hao Peng, Jianxin Li:
Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization. - Aniket Das, Dheeraj Nagaraj:
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation. - Yue Song, Andy Keller, Nicu Sebe, Max Welling:
Flow Factorized Representation Learning. - Yan Scholten, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann:
Hierarchical Randomized Smoothing. - Subhro Roy, Samuel Thomson, Tongfei Chen, Richard Shin, Adam Pauls, Jason Eisner, Benjamin Van Durme:
BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsing. - Thomas Pethick, Wanyun Xie, Volkan Cevher:
Stable Nonconvex-Nonconcave Training via Linear Interpolation. - Wenliang Zhao, Lujia Bai, Yongming Rao, Jie Zhou, Jiwen Lu:
UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models. - Jianhao Zhang, Shihan Ma, Peihong Liu, Jinhui Yuan:
Coop: Memory is not a Commodity. - Rattana Pukdee, Dylan Sam, J. Zico Kolter, Maria-Florina Balcan, Pradeep Ravikumar:
Learning with Explanation Constraints. - Ioannis Anagnostides, Tuomas Sandholm:
On the Interplay between Social Welfare and Tractability of Equilibria. - Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alex Dimakis, Sanjay Shakkottai:
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models. - Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth:
Maximum State Entropy Exploration using Predecessor and Successor Representations. - Yang Li, Jinpei Guo, Runzhong Wang, Junchi Yan:
From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization. - Benjamin S. Ruben, Cengiz Pehlevan:
Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles. - Joseph Suarez, David Bloomin, Kyoung Whan Choe, Hao Xiang Li, Ryan Sullivan, Nishaanth Kanna, Daniel Scott, Rose S. Shuman, Herbie Bradley, Louis Castricato, Phillip Isola, Chenghui Yu, Yuhao Jiang, Qimai Li, Jiaxin Chen, Xiaolong Zhu:
Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning. - Lin Li, Jun Xiao, Guikun Chen, Jian Shao, Yueting Zhuang, Long Chen:
Zero-shot Visual Relation Detection via Composite Visual Cues from Large Language Models. - Yuchen Zhuang, Yue Yu, Kuan Wang, Haotian Sun, Chao Zhang:
ToolQA: A Dataset for LLM Question Answering with External Tools. - Chen Fan, Gaspard Choné-Ducasse, Mark Schmidt, Christos Thrampoulidis:
BiSLS/SPS: Auto-tune Step Sizes for Stable Bi-level Optimization. - Maya Okawa, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka:
Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task. - Felipe Nuti, Tim Franzmeyer, João F. Henriques:
Extracting Reward Functions from Diffusion Models. - Tianchi Liu, Kong Aik Lee, Qiongqiong Wang, Haizhou Li:
Disentangling Voice and Content with Self-Supervision for Speaker Recognition. - Zihao Zhou, Rose Yu:
Automatic Integration for Spatiotemporal Neural Point Processes. - Jiaqi Zhang, Kristjan H. Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Soft Interventions. - Arnab Kumar Mondal, Siba Smarak Panigrahi, Oumar Kaba, Sai Mudumba, Siamak Ravanbakhsh:
Equivariant Adaptation of Large Pretrained Models. - Triantafyllos Afouras, Effrosyni Mavroudi, Tushar Nagarajan, Huiyu Wang, Lorenzo Torresani:
HT-Step: Aligning Instructional Articles with How-To Videos. - Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi:
Provable Training for Graph Contrastive Learning. - Dengwei Zhao, Shikui Tu, Lei Xu:
Generalized Weighted Path Consistency for Mastering Atari Games. - Niklas Muennighoff, Alexander M. Rush, Boaz Barak, Teven Le Scao, Nouamane Tazi, Aleksandra Piktus, Sampo Pyysalo, Thomas Wolf, Colin A. Raffel:
Scaling Data-Constrained Language Models. - David Abel, André Barreto, Benjamin Van Roy, Doina Precup, Hado Philip van Hasselt, Satinder Singh:
A Definition of Continual Reinforcement Learning. - Minkyu Choi, Kuan Han, Xiaokai Wang, Yizhen Zhang, Zhongming Liu:
A Dual-Stream Neural Network Explains the Functional Segregation of Dorsal and Ventral Visual Pathways in Human Brains. - Tianwei Ni, Michel Ma, Benjamin Eysenbach, Pierre-Luc Bacon:
When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment. - Maryam Aliakbarpour, Mark Bun, Adam Smith:
Hypothesis Selection with Memory Constraints. - Ido Greenberg, Netanel Yannay, Shie Mannor:
Optimization or Architecture: How to Hack Kalman Filtering. - Abishek Sankararaman, Balakrishnan Narayanaswamy:
Online robust non-stationary estimation. - Antonín Vobecký, Oriane Siméoni, David Hurych, Spyridon Gidaris, Andrei Bursuc, Patrick Pérez, Josef Sivic:
POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images. - Gergely Flamich, Stratis Markou, José Miguel Hernández-Lobato:
Faster Relative Entropy Coding with Greedy Rejection Coding. - Xing Wei, Anjia Cao, Funing Yang, Zhiheng Ma:
Sparse Parameterization for Epitomic Dataset Distillation. - Junkun Yuan, Xinyu Zhang, Hao Zhou, Jian Wang, Zhongwei Qiu, Zhiyin Shao, Shaofeng Zhang, Sifan Long, Kun Kuang, Kun Yao, Junyu Han, Errui Ding, Lanfen Lin, Fei Wu, Jingdong Wang:
HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception. - Mateusz Olko, Michal Zajac, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Lukasz Kucinski, Piotr Milos:
Trust Your 𝛁: Gradient-based Intervention Targeting for Causal Discovery. - Yuseung Lee, Kunho Kim, Hyunjin Kim, Minhyuk Sung:
SyncDiffusion: Coherent Montage via Synchronized Joint Diffusions. - Spyridon Kondylatos, Ioannis Prapas, Gustau Camps-Valls, Ioannis Papoutsis:
Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean. - Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri:
Deep learning with kernels through RKHM and the Perron-Frobenius operator. - Max Torop, Aria Masoomi, Davin Hill, Kivanç Köse, Stratis Ioannidis, Jennifer G. Dy:
SmoothHess: ReLU Network Feature Interactions via Stein's Lemma. - Andrej Bauer, Matej Petkovic, Ljupco Todorovski:
MLFMF: Data Sets for Machine Learning for Mathematical Formalization. - Stephanie Fu, Netanel Tamir, Shobhita Sundaram, Lucy Chai, Richard Zhang, Tali Dekel, Phillip Isola:
DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data. - Siu Lun Chau, Krikamol Muandet, Dino Sejdinovic:
Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models. - Satoshi Tsutsui, Winnie Pang, Bihan Wen:
WBCAtt: A White Blood Cell Dataset Annotated with Detailed Morphological Attributes. - Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Kompella, Zhangyang Wang:
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. - Quentin Delfosse, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction. - Geyu Liang, Naichen Shi, Raed Al Kontar, Salar Fattahi:
Personalized Dictionary Learning for Heterogeneous Datasets. - Jun Wu, Lisa Ainsworth, Andrew Leakey, Haixun Wang, Jingrui He:
Graph-Structured Gaussian Processes for Transferable Graph Learning. - Hariharan Manikandan, Yiding Jiang, J. Zico Kolter:
Language Models are Weak Learners. - Ziyi Wu, Jingyu Hu, Wuyue Lu, Igor Gilitschenski, Animesh Garg:
SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models. - Yutong Kou, Jin Gao, Bing Li, Gang Wang, Weiming Hu, Yizheng Wang, Liang Li:
ZoomTrack: Target-aware Non-uniform Resizing for Efficient Visual Tracking. - Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. Hermann, Andrew K. Lampinen, Simon Kornblith:
Improving neural network representations using human similarity judgments. - Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery. - Jie Hao, Kaiyi Ji, Mingrui Liu:
Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm. - Bipasha Sen, Gaurav Singh, Aditya Agarwal, Rohith Agaram, K. Madhava Krishna, Srinath Sridhar:
HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork. - Kate Sanders, David Etter, Reno Kriz, Benjamin Van Durme:
MultiVENT: Multilingual Videos of Events and Aligned Natural Text. - Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan D. Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu:
GEO-Bench: Toward Foundation Models for Earth Monitoring. - Chengcheng Wang, Wei He, Ying Nie, Jianyuan Guo, Chuanjian Liu, Yunhe Wang, Kai Han:
Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanism. - Zheng Zhang, Junxiang Wang, Liang Zhao:
Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First. - Jayadev Acharya, Clément L. Canonne, Ziteng Sun, Himanshu Tyagi:
Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints. - Junsheng Zhou, Baorui Ma, Wenyuan Zhang, Yi Fang, Yu-Shen Liu, Zhizhong Han:
Differentiable Registration of Images and LiDAR Point Clouds with VoxelPoint-to-Pixel Matching. - Connor Toups, Rishi Bommasani, Kathleen Creel, Sarah H. Bana, Dan Jurafsky, Percy Liang:
Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes. - Shitao Tang, Fuyang Zhang, Jiacheng Chen, Peng Wang, Yasutaka Furukawa:
MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion. - Lucrezia Valeriani, Diego Doimo, Francesca Cuturello, Alessandro Laio, Alessio Ansuini, Alberto Cazzaniga:
The geometry of hidden representations of large transformer models. - Guangyu Shen, Siyuan Cheng, Guanhong Tao, Kaiyuan Zhang, Yingqi Liu, Shengwei An, Shiqing Ma, Xiangyu Zhang:
Django: Detecting Trojans in Object Detection Models via Gaussian Focus Calibration. - Fatih Dinc, Adam Shai, Mark Schnitzer, Hidenori Tanaka:
CORNN: Convex optimization of recurrent neural networks for rapid inference of neural dynamics. - Rufeng Xiao, Yuze Ge, Rujun Jiang, Yifan Yan:
A Unified Framework for Rank-based Loss Minimization. - Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton:
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. - Han Liu, Zhi Xu, Xiaotong Zhang, Feng Zhang, Fenglong Ma, Hongyang Chen, Hong Yu, Xianchao Zhang:
HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text. - Jiawei Fan, Chao Li, Xiaolong Liu, Meina Song, Anbang Yao:
Augmentation-free Dense Contrastive Distillation for Efficient Semantic Segmentation. - Jiashuo Liu, Tianyu Wang, Peng Cui, Hongseok Namkoong:
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets. - Aniruddha Sen, Christine Task, Dhruv Kapur, Gary Howarth, Karan Bhagat:
Diverse Community Data for Benchmarking Data Privacy Algorithms. - Albert Tseng, Tao Yu, Toni J. B. Liu, Christopher De Sa:
Coneheads: Hierarchy Aware Attention. - Geonu Kim, Byunggook Na, Gunhee Kim, Hyuntae Cho, Seungjin Kang, Hee Sun Lee, Saerom Choi, Heejae Kim, Seungwon Lee, Yongdeok Kim:
Benchmark of Machine Learning Force Fields for Semiconductor Simulations: Datasets, Metrics, and Comparative Analysis. - Aoxiang Zhang, Yu Ran, Weixuan Tang, Yuan-Gen Wang:
Vulnerabilities in Video Quality Assessment Models: The Challenge of Adversarial Attacks. - Hao Hu, Yiqin Yang, Jianing Ye, Ziqing Mai, Chongjie Zhang:
Unsupervised Behavior Extraction via Random Intent Priors. - Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Yakir Oz, Yaniv Nikankin, Michal Irani:
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses. - Denis Blessing, Onur Celik, Xiaogang Jia, Moritz Reuss, Maximilian Xiling Li, Rudolf Lioutikov, Gerhard Neumann:
Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills. - Yifan Zhang, Qijian Zhang, Junhui Hou, Yixuan Yuan, Guoliang Xing:
Unleash the Potential of Image Branch for Cross-modal 3D Object Detection. - Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu:
Model Sparsity Can Simplify Machine Unlearning. - Zhenchao Jin, Xiaowei Hu, Lingting Zhu, Luchuan Song, Li Yuan, Lequan Yu:
IDRNet: Intervention-Driven Relation Network for Semantic Segmentation. - Dayal Singh Kalra, Maissam Barkeshli:
Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width. - Gleb Rodionov, Liudmila Prokhorenkova:
Neural Algorithmic Reasoning Without Intermediate Supervision. - Sangha Park, Jisoo Mok, Dahuin Jung, Saehyung Lee, Sungroh Yoon:
On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection. - Zhongzhou Liu, Yuan Fang, Min Wu:
Estimating Propensity for Causality-based Recommendation without Exposure Data. - Akshaykumar Gattani, Sharath Raghvendra, Pouyan Shirzadian:
A Robust Exact Algorithm for the Euclidean Bipartite Matching Problem. - Zhaoyu Chen, Bo Li, Shuang Wu, Kaixun Jiang, Shouhong Ding, Wenqiang Zhang:
Content-based Unrestricted Adversarial Attack. - Jia Lin Hau, Erick Delage, Mohammad Ghavamzadeh, Marek Petrik:
On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes. - Shuo Chen, Jindong Gu, Zhen Han, Yunpu Ma, Philip H. S. Torr, Volker Tresp:
Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models. - Nino Scherrer, Claudia Shi, Amir Feder, David M. Blei:
Evaluating the Moral Beliefs Encoded in LLMs. - Boya Zhang, Weijian Luo, Zhihua Zhang:
Enhancing Adversarial Robustness via Score-Based Optimization. - Giorgio Giannone, Akash Srivastava, Ole Winther, Faez Ahmed:
Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation. - Jon Schneider, Julian Zimmert:
Optimal cross-learning for contextual bandits with unknown context distributions. - Chengjie Wu, Pingzhong Tang, Jun Yang, Yujing Hu, Tangjie Lv, Changjie Fan, Chongjie Zhang:
Conservative Offline Policy Adaptation in Multi-Agent Games. - Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh:
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information. - Yuxin Pan, Yize Chen, Fangzhen Lin:
Adjustable Robust Reinforcement Learning for Online 3D Bin Packing. - Harit Vishwakarma, Heguang Lin, Frederic Sala, Ramya Korlakai Vinayak:
Promises and Pitfalls of Threshold-based Auto-labeling. - Guohao Li, Hasan Hammoud, Hani Itani, Dmitrii Khizbullin, Bernard Ghanem:
CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society. - Abhinav Nippani, Dongyue Li, Haotian Ju, Haris K. Koutsopoulos, Hongyang R. Zhang:
Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis. - Jingyang Xiang, Siqi Li, Jun Chen, Guang Dai, Shipeng Bai, Yukai Ma, Yong Liu:
SUBP: Soft Uniform Block Pruning for 1×N Sparse CNNs Multithreading Acceleration. - Mufang Ying, Koulik Khamaru, Cun-Hui Zhang:
Adaptive Linear Estimating Equations. - Jiawei Huang, Niao He:
Robust Knowledge Transfer in Tiered Reinforcement Learning. - Haolin Liu, Chen-Yu Wei, Julian Zimmert:
Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits. - Dhruba Ghosh, Hannaneh Hajishirzi, Ludwig Schmidt:
GenEval: An object-focused framework for evaluating text-to-image alignment. - Moshe Shenfeld, Katrina Ligett:
Generalization in the Face of Adaptivity: A Bayesian Perspective. - Haochuan Li, Alexander Rakhlin, Ali Jadbabaie:
Convergence of Adam Under Relaxed Assumptions. - Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher:
On the Convergence of Encoder-only Shallow Transformers. - Mason L. Wang, Samuel Clarke, Jui-Hsien Wang, Ruohan Gao, Jiajun Wu:
SoundCam: A Dataset for Finding Humans Using Room Acoustics. - Xiaohan Zhao, Hualin Zhang, Zhouyuan Huo, Bin Gu:
Accelerated On-Device Forward Neural Network Training with Module-Wise Descending Asynchronism. - Chao Chen, Zhihang Fu, Kai Liu, Ze Chen, Mingyuan Tao, Jieping Ye:
Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection. - Meyer Scetbon, Michal Klein, Giovanni Palla, Marco Cuturi:
Unbalanced Low-rank Optimal Transport Solvers. - Changdae Oh, Junhyuk So, Hoyoon Byun, YongTaek Lim, Minchul Shin, Jong-June Jeon, Kyungwoo Song:
Geodesic Multi-Modal Mixup for Robust Fine-Tuning. - Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava:
Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time. - Samuel Pfrommer, Brendon G. Anderson, Julien Piet, Somayeh Sojoudi:
Asymmetric Certified Robustness via Feature-Convex Neural Networks. - Weiwei Kong, Andrés Muñoz Medina:
A Unified Fast Gradient Clipping Framework for DP-SGD. - Xiangsen Wang, Haoran Xu, Yinan Zheng, Xianyuan Zhan:
Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value Regularization. - Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, Michael Lingzhi Li:
Benchmarking Large Language Models on CMExam - A comprehensive Chinese Medical Exam Dataset. - William Merrill, Ashish Sabharwal:
A Logic for Expressing Log-Precision Transformers. - Taoran Fang, Yunchao Zhang, Yang Yang, Chunping Wang, Lei Chen:
Universal Prompt Tuning for Graph Neural Networks. - Lijun Zhang, Peng Zhao, Zhen-Hua Zhuang, Tianbao Yang, Zhi-Hua Zhou:
Stochastic Approximation Approaches to Group Distributionally Robust Optimization. - Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park:
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks. - Wei Dong, Dawei Yan, Zhijun Lin, Peng Wang:
Efficient Adaptation of Large Vision Transformer via Adapter Re-Composing. - Tamás Sarlós, Xingyou Song, David P. Woodruff, Richard Zhang:
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. - Davide Carbone, Mengjian Hua, Simon Coste, Eric Vanden-Eijnden:
Efficient Training of Energy-Based Models Using Jarzynski Equality. - Chao Ma, Cheng Zhang:
High Precision Causal Model Evaluation with Conditional Randomization. - Julien Grand-Clément, Marek Petrik:
Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor. - Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish, Jean-Francois Ton:
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits. - Lijun Yu, Yong Cheng, Zhiruo Wang, Vivek Kumar, Wolfgang Macherey, Yanping Huang, David A. Ross, Irfan Essa, Yonatan Bisk, Ming-Hsuan Yang, Kevin P. Murphy, Alexander G. Hauptmann, Lu Jiang:
SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs. - Benjamin Scellier, Maxence Ernoult, Jack D. Kendall, Suhas Kumar:
Energy-based learning algorithms for analog computing: a comparative study. - Shai Ben-David, Alex Bie, Gautam Kamath, Tosca Lechner:
Distribution Learnability and Robustness. - Dhawal Gupta, Yash Chandak, Scott M. Jordan, Philip S. Thomas, Bruno C. da Silva:
Behavior Alignment via Reward Function Optimization. - Dongsheng Wang, Miaoge Li, Xinyang Liu, Mingsheng Xu, Bo Chen, Hanwang Zhang:
Tuning Multi-mode Token-level Prompt Alignment across Modalities. - Taeho Yoon, Kibeom Myoung, Keon Lee, Jaewoong Cho, Albert No, Ernest K. Ryu:
Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback. - Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noé, Ryota Tomioka:
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics. - Zicheng Liu, Siyuan Li, Ge Wang, Lirong Wu, Cheng Tan, Stan Z. Li:
Harnessing Hard Mixed Samples with Decoupled Regularizer. - Eoin M. Kenny, Weipeng Huang:
The Utility of "Even if" Semifactual Explanation to Optimise Positive Outcomes. - Ziyi Yin, Muchao Ye, Tianrong Zhang, Tianyu Du, Jinguo Zhu, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma:
VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models. - Christoph Hertrich, Yixin Tao, László A. Végh:
Mode Connectivity in Auction Design. - Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov:
Katakomba: Tools and Benchmarks for Data-Driven NetHack. - Peter Súkeník, Marco Mondelli, Christoph H. Lampert:
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model. - Shuwei Shao, Zhongcai Pei, Xingming Wu, Zhong Liu, Weihai Chen, Zhengguo Li:
IEBins: Iterative Elastic Bins for Monocular Depth Estimation. - Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason D. Lee, Danqi Chen, Sanjeev Arora:
Fine-Tuning Language Models with Just Forward Passes. - Gang Zhang, Junnan Chen, Guohuan Gao, Jianmin Li, Xiaolin Hu:
HEDNet: A Hierarchical Encoder-Decoder Network for 3D Object Detection in Point Clouds. - Jinyuan Jia, Zhuowen Yuan, Dinuka Sahabandu, Luyao Niu, Arezoo Rajabi, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran:
FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning. - Yuan Jiang, Zhiguang Cao, Yaoxin Wu, Wen Song, Jie Zhang:
Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift. - Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari:
Module-wise Training of Neural Networks via the Minimizing Movement Scheme. - Yongbo Chen, Hanna Kurniawati:
POMDP Planning for Object Search in Partially Unknown Environment. - Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao:
On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making. - Beining Yang, Kai Wang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Hao Tang, Yang You, Jianxin Li:
Does Graph Distillation See Like Vision Dataset Counterpart? - Pavel Kolev, Georg Martius, Michael Muehlebach:
Online Learning under Adversarial Nonlinear Constraints. - Woojun Kim, Yongjae Shin, Jongeui Park, Youngchul Sung:
Sample-Efficient and Safe Deep Reinforcement Learning via Reset Deep Ensemble Agents. - Bhishma Dedhia, Michael Chang, Jake Snell, Tom Griffiths, Niraj K. Jha:
Im-Promptu: In-Context Composition from Image Prompts. - Aleksandr Podkopaev, Aaditya Ramdas:
Sequential Predictive Two-Sample and Independence Testing. - Youzhi Luo, Chengkai Liu, Shuiwang Ji:
Towards Symmetry-Aware Generation of Periodic Materials. - Lora Aroyo, Alex S. Taylor, Mark Díaz, Christopher Homan, Alicia Parrish, Gregory Serapio-García, Vinodkumar Prabhakaran, Ding Wang:
DICES Dataset: Diversity in Conversational AI Evaluation for Safety. - Cathy Yuanchen Li, Emily Wenger, Zeyuan Allen-Zhu, François Charton, Kristin E. Lauter:
SALSA VERDE: a machine learning attack on LWE with sparse small secrets. - Xing Han, Tongzheng Ren, Tan Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho:
Designing Robust Transformers using Robust Kernel Density Estimation. - Josh Gardner, Zoran Popovic, Ludwig Schmidt:
Benchmarking Distribution Shift in Tabular Data with TableShift. - Kunhao Liu, Fangneng Zhan, Jiahui Zhang, Muyu Xu, Yingchen Yu, Abdulmotaleb El-Saddik, Christian Theobalt, Eric P. Xing, Shijian Lu:
Weakly Supervised 3D Open-vocabulary Segmentation. - Travis Dick, Jennifer Gillenwater, Matthew Joseph:
Better Private Linear Regression Through Better Private Feature Selection. - Emile Mathieu, Vincent Dutordoir, Michael J. Hutchinson, Valentin De Bortoli, Yee Whye Teh, Richard E. Turner:
Geometric Neural Diffusion Processes. - Yiheng Lin, James A. Preiss, Emile Anand, Yingying Li, Yisong Yue, Adam Wierman:
Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations. - Pascal Leroy, Pablo G. Morato, Jonathan Pisane, Athanasios Kolios, Damien Ernst:
IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL. - Shicheng Liu, Minghui Zhu:
Learning Multi-agent Behaviors from Distributed and Streaming Demonstrations. - Yulei Qin, Xingyu Chen, Yunhang Shen, Chaoyou Fu, Yun Gu, Ke Li, Xing Sun, Rongrong Ji:
CAPro: Webly Supervised Learning with Cross-modality Aligned Prototypes. - Daesol Cho, Seungjae Lee, H. Jin Kim:
Diversify & Conquer: Outcome-directed Curriculum RL via Out-of-Distribution Disagreement. - Shang Liu, Zhongze Cai, Xiaocheng Li:
Distribution-Free Model-Agnostic Regression Calibration via Nonparametric Methods. - Qiuxia Lin, Kerui Gu, Linlin Yang, Angela Yao:
Synthetic-to-Real Pose Estimation with Geometric Reconstruction. - Wei Fang, Zhaofei Yu, Zhaokun Zhou, Ding Chen, Yanqi Chen, Zhengyu Ma, Timothée Masquelier, Yonghong Tian:
Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies. - Zihui Xue, Kristen Grauman:
Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment. - Stephan Rabanser, Anvith Thudi, Abhradeep Guha Thakurta, Krishnamurthy Dvijotham, Nicolas Papernot:
Training Private Models That Know What They Don't Know. - Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D. Manning, Stefano Ermon, Chelsea Finn:
Direct Preference Optimization: Your Language Model is Secretly a Reward Model. - Mingzhen He, Fan He, Ruikai Yang, Xiaolin Huang:
Diffusion Representation for Asymmetric Kernels via Magnetic Transform. - Pritam Sarkar, Ahmad Beirami, Ali Etemad:
Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts. - Jonggyu Jang, Sangwoo Oh, Youjin Kim, Dongmin Seo, Youngchol Choi, Hyun Jong Yang:
M2SODAI: Multi-Modal Maritime Object Detection Dataset With RGB and Hyperspectral Image Sensors. - Morteza Boroun, Erfan Yazdandoost Hamedani, Afrooz Jalilzadeh:
Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems. - Peiwen Yuan, Xinglin Wang, Jiayi Shi, Bin Sun, Yiwei Li:
Better Correlation and Robustness: A Distribution-Balanced Self-Supervised Learning Framework for Automatic Dialogue Evaluation. - Ke Yi, Yansen Wang, Kan Ren, Dongsheng Li:
Learning Topology-Agnostic EEG Representations with Geometry-Aware Modeling. - Shuli Jiang, Pranay Sharma, Gauri Joshi:
Correlation Aware Sparsified Mean Estimation Using Random Projection. - Jongmin Lee, Ernest Ryu:
Accelerating Value Iteration with Anchoring. - Yang Liu, Feng Wang, Naiyan Wang, Zhaoxiang Zhang:
Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality Fusion. - Kushal Tirumala, Daniel Simig, Armen Aghajanyan, Ari Morcos:
D4: Improving LLM Pretraining via Document De-Duplication and Diversification. - Alexander Immer, Emanuele Palumbo, Alexander Marx, Julia E. Vogt:
Effective Bayesian Heteroscedastic Regression with Deep Neural Networks. - Parker Knight, Rui Duan:
Multi-task learning with summary statistics. - Amin Nejatbakhsh, Isabel Garon, Alex Williams:
Estimating Noise Correlations Across Continuous Conditions With Wishart Processes. - Chenyu Zheng, Guoqiang Wu, Chongxuan Li:
Toward Understanding Generative Data Augmentation. - Xiaoying Xing, Mingfu Liang, Ying Wu:
TOA: Task-oriented Active VQA. - Taoli Zheng, Linglingzhi Zhu, Anthony Man-Cho So, Jose H. Blanchet, Jiajin Li:
Universal Gradient Descent Ascent Method for Nonconvex-Nonconcave Minimax Optimization. - Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Chongxuan Li, Ngai-Man Cheung, Min Lin:
On Evaluating Adversarial Robustness of Large Vision-Language Models. - Runpeng Yu, Xinchao Wang:
Generator Born from Classifier. - Badri N. Patro, Vijay Srinivas Agneeswaran:
Scattering Vision Transformer: Spectral Mixing Matters. - Huining Yuan, Hongkun Dou, Xingyu Jiang, Yue Deng:
Task-aware world model learning with meta weighting via bi-level optimization. - Di Liu, Anastasis Stathopoulos, Qilong Zhangli, Yunhe Gao, Dimitris N. Metaxas:
LEPARD: Learning Explicit Part Discovery for 3D Articulated Shape Reconstruction. - Saber Sheybani, Himanshu Hansaria, Justin Wood, Linda B. Smith, Zoran Tiganj:
Curriculum Learning With Infant Egocentric Videos. - Shyam Sudhakaran, Miguel González Duque, Matthias Freiberger, Claire Glanois, Elias Najarro, Sebastian Risi:
MarioGPT: Open-Ended Text2Level Generation through Large Language Models. - William Brown, Jon Schneider, Kiran Vodrahalli:
Is Learning in Games Good for the Learners? - Lorenzo Noci, Chuning Li, Mufan Bill Li, Bobby He, Thomas Hofmann, Chris J. Maddison, Dan Roy:
The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit. - Tingyu Weng, Jun Xiao, Haiyong Jiang:
Decompose Novel into Known: Part Concept Learning For 3D Novel Class Discovery. - Hamza Tahir Chaudhry, Jacob A. Zavatone-Veth, Dmitry Krotov, Cengiz Pehlevan:
Long Sequence Hopfield Memory. - Nuoya Xiong, Yihan Du, Longbo Huang:
Provably Safe Reinforcement Learning with Step-wise Violation Constraints. - Tracey Mills, Josh Tenenbaum, Samuel J. Cheyette:
Human spatiotemporal pattern learning as probabilistic program synthesis. - Bo Li, Fangxiao Wang, Yu Zhou:
Fair Allocation of Indivisible Chores: Beyond Additive Costs. - Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright:
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. - Zhepei Wei, Chuanhao Li, Haifeng Xu, Hongning Wang:
Incentivized Communication for Federated Bandits. - Junfeng Guo, Yiming Li, Lixu Wang, Shu-Tao Xia, Heng Huang, Cong Liu, Bo Li:
Domain Watermark: Effective and Harmless Dataset Copyright Protection is Closed at Hand. - Luca A. Lanzendörfer, Florian Grötschla, Emil Funke, Roger Wattenhofer:
DISCO-10M: A Large-Scale Music Dataset. - Changyeon Kim, Younggyo Seo, Hao Liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee:
Guide Your Agent with Adaptive Multimodal Rewards. - Jun Chen, Hong Chen, Bin Gu, Hao Deng:
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization. - Mingxuan Zhang, Yan Sun, Faming Liang:
Sparse Deep Learning for Time Series Data: Theory and Applications. - Pini Zilber, Boaz Nadler:
Imbalanced Mixed Linear Regression. - Ziang Li, Mengda Yang, Yaxin Liu, Juan Wang, Hongxin Hu, Wenzhe Yi, Xiaoyang Xu:
GAN You See Me? Enhanced Data Reconstruction Attacks against Split Inference. - Amirkeivan Mohtashami, Martin Jaggi:
Random-Access Infinite Context Length for Transformers. - Xiaotian Liu, Héctor Palacios, Christian Muise:
Egocentric Planning for Scalable Embodied Task Achievement. - Haoxuan Li, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Zhi Geng, Fuli Feng, Xiangnan He, Peng Wu:
Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach. - Jiyao Zhang, Mingdong Wu, Hao Dong:
Generative Category-level Object Pose Estimation via Diffusion Models. - Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin:
On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective. - Weijia Wu, Yuzhong Zhao, Hao Chen, Yuchao Gu, Rui Zhao, Yefei He, Hong Zhou, Mike Zheng Shou, Chunhua Shen:
DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models. - Omid Sadeghi, Maryam Fazel:
No-Regret Online Prediction with Strategic Experts. - Yunhua Zhang, Hazel Doughty, Cees Snoek:
Learning Unseen Modality Interaction. - Pulkit Verma, Rushang Karia, Siddharth Srivastava:
Autonomous Capability Assessment of Sequential Decision-Making Systems in Stochastic Settings. - Alessio Russo, Alexandre Proutière:
Model-Free Active Exploration in Reinforcement Learning. - Yatin Dandi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro, Lenka Zdeborová:
Universality laws for Gaussian mixtures in generalized linear models. - Kexun Zhang, Danqing Wang, Jingtao Xia, William Yang Wang, Lei Li:
ALGO: Synthesizing Algorithmic Programs with Generated Oracle Verifiers. - Moni Naor, Kobbi Nissim, Uri Stemmer, Chao Yan:
Private Everlasting Prediction. - Thomas Fel, Victor Boutin, Louis Béthune, Rémi Cadène, Mazda Moayeri, Léo Andéol, Mathieu Chalvidal, Thomas Serre:
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation. - Fenja Falta, Christoph Großbröhmer, Alessa Hering, Alexander Bigalke, Mattias P. Heinrich:
Lung250M-4B: A Combined 3D Dataset for CT- and Point Cloud-Based Intra-Patient Lung Registration. - Zhenbang Wu, Huaxiu Yao, David M. Liebovitz, Jimeng Sun:
An Iterative Self-Learning Framework for Medical Domain Generalization. - Federico Matteucci, Vadim Arzamasov, Klemens Böhm:
A benchmark of categorical encoders for binary classification. - Dmitry Yarotsky:
Structure of universal formulas. - Hailin Zhang, Yujing Wang, Qi Chen, Ruiheng Chang, Ting Zhang, Ziming Miao, Yingyan Hou, Yang Ding, Xupeng Miao, Haonan Wang, Bochen Pang, Yuefeng Zhan, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Xing Xie, Mao Yang, Bin Cui:
Model-enhanced Vector Index. - Tianxiang Gao, Xiaokai Huo, Hailiang Liu, Hongyang Gao:
Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models. - Laura Manduchi, Moritz Vandenhirtz, Alain Ryser, Julia E. Vogt:
Tree Variational Autoencoders. - Yihong Sun, Bharath Hariharan:
Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes. - Chunting Zhou, Pengfei Liu, Puxin Xu, Srinivasan Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Omer Levy:
LIMA: Less Is More for Alignment. - Wenzhuo Zhou:
Bi-Level Offline Policy Optimization with Limited Exploration. - Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W. Fitzgibbon, Dominic Masters:
Generating QM1B with PySCFIPU. - Chendi Wang, Buxin Su, Jiayuan Ye, Reza Shokri, Weijie J. Su:
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via f-Differential Privacy. - Srinivasan Arunachalam, Vojtech Havlícek, Louis Schatzki:
On the Role of Entanglement and Statistics in Learning. - Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhi-Ming Ma, Shengchao Liu:
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. - Xuming An, Li Shen, Han Hu, Yong Luo:
Federated Learning with Manifold Regularization and Normalized Update Reaggregation. - Tongxin Yin, Reilly Raab, Mingyan Liu, Yang Liu:
Long-Term Fairness with Unknown Dynamics. - Andy Zhou, Samuel Li, Pranav Sriram, Xiang Li, Jiahua Dong, Ansh Sharma, Yuanyi Zhong, Shirui Luo, Volodymyr V. Kindratenko, George Heintz, Christopher Zallek, Yu-Xiong Wang:
YouTubePD: A Multimodal Benchmark for Parkinson's Disease Analysis. - Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu, Jacek Tabor:
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training. - Maxence Noble, Valentin De Bortoli, Arnaud Doucet, Alain Durmus:
Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters. - Jan Dubinski, Stanislaw Pawlak, Franziska Boenisch, Tomasz Trzcinski, Adam Dziedzic:
Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders. - Ilyes Batatia, Mario Geiger, Jose M. Munoz, Tess E. Smidt, Lior Silberman, Christoph Ortner:
A General Framework for Equivariant Neural Networks on Reductive Lie Groups. - Weikang Bian, Zhaoyang Huang, Xiaoyu Shi, Yitong Dong, Yijin Li, Hongsheng Li:
Context-PIPs: Persistent Independent Particles Demands Context Features. - Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
GloptiNets: Scalable Non-Convex Optimization with Certificates. - Jerone Theodore Alexander Andrews, Dora Zhao, William Thong, Apostolos Modas, Orestis Papakyriakopoulos, Alice Xiang:
Ethical Considerations for Responsible Data Curation. - Cheng Cheng, Lin Song, Ruoyi Xue, Hang Wang, Hongbin Sun, Yixiao Ge, Ying Shan:
Meta-Adapter: An Online Few-shot Learner for Vision-Language Model. - Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi:
Taming Local Effects in Graph-based Spatiotemporal Forecasting. - Valentino Maiorca, Luca Moschella, Antonio Norelli, Marco Fumero, Francesco Locatello, Emanuele Rodolà:
Latent Space Translation via Semantic Alignment. - Sarah M. Hooper, Mayee F. Chen, Khaled Saab, Kush Bhatia, Curtis P. Langlotz, Christopher Ré:
A case for reframing automated medical image classification as segmentation. - Wonje Choi, Woo Kyung Kim, Seunghyun Kim, Honguk Woo:
Efficient Policy Adaptation with Contrastive Prompt Ensemble for Embodied Agents. - Russell Hart, Linlin Yu, Yifei Lou, Feng Chen:
Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization. - Seiyun Shin, Ilan Shomorony, Han Zhao:
Efficient Learning of Linear Graph Neural Networks via Node Subsampling. - Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu:
DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics. - James Cheshire, Vincent Laurent, Stéphan Clémençon:
Active Bipartite Ranking. - Rylan Schaeffer, Brando Miranda, Sanmi Koyejo:
Are Emergent Abilities of Large Language Models a Mirage? - Gen Li, Wenhao Zhan, Jason D. Lee, Yuejie Chi, Yuxin Chen:
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning. - Behrooz Tahmasebi, Stefanie Jegelka:
The Exact Sample Complexity Gain from Invariances for Kernel Regression. - Hao Zhang, Tianyuan Dai, Yanbo Xu, Yu-Wing Tai, Chi-Keung Tang:
FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models. - Anurag Ghosh, Vaibhav Balloli, Akshay Nambi, Aditya Singh, Tanuja Ganu:
Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception. - Sumedh Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti:
RoboCLIP: One Demonstration is Enough to Learn Robot Policies. - Yihe Wang, Yu Han, Haishuai Wang, Xiang Zhang:
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series. - Ye Yuan, Can Chen, Zixuan Liu, Willie Neiswanger, Xue (Steve) Liu:
Importance-aware Co-teaching for Offline Model-based Optimization. - Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander J. Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang:
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias. - Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye:
GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation. - Georgios Kaissis, Alexander Ziller, Stefan Kolek, Anneliese Riess, Daniel Rueckert:
Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning. - Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause:
Stochastic Approximation Algorithms for Systems of Interacting Particles. - Zhenmei Shi, Junyi Wei, Yingyu Liang:
Provable Guarantees for Neural Networks via Gradient Feature Learning. - Seungjoo Shin, Jaesik Park:
Binary Radiance Fields. - Alicia Curth, Alan Jeffares, Mihaela van der Schaar:
A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning. - Qizhi Pei, Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Kun He, Tie-Yan Liu, Rui Yan:
FABind: Fast and Accurate Protein-Ligand Binding. - Yusong Wang, Shaoning Li, Tong Wang, Bin Shao, Nanning Zheng, Tie-Yan Liu:
Geometric Transformer with Interatomic Positional Encoding. - Matthew Niedoba, Jonathan Wilder Lavington, Yunpeng Liu, Vasileios Lioutas, Justice Sefas, Xiaoxuan Liang, Dylan Green, Setareh Dabiri, Berend Zwartsenberg, Adam Scibior, Frank Wood:
A Diffusion-Model of Joint Interactive Navigation. - Kun-Yu Lin, Jia-Run Du, Yipeng Gao, Jiaming Zhou, Wei-Shi Zheng:
Diversifying Spatial-Temporal Perception for Video Domain Generalization. - Andreas Auer, Martin Gauch, Daniel Klotz, Sepp Hochreiter:
Conformal Prediction for Time Series with Modern Hopfield Networks. - Haoyi Duan, Yan Xia, Mingze Zhou, Li Tang, Jieming Zhu, Zhou Zhao:
Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks. - Alexander Schlögl, Nora Hofer, Rainer Böhme:
Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks. - Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj:
Learning via Wasserstein-Based High Probability Generalisation Bounds. - Metod Jazbec, James Urquhart Allingham, Dan Zhang, Eric T. Nalisnick:
Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity. - Zhijian Duan, Haoran Sun, Yurong Chen, Xiaotie Deng:
A Scalable Neural Network for DSIC Affine Maximizer Auction Design. - Zhongwei Wan, Che Liu, Mi Zhang, Jie Fu, Benyou Wang, Sibo Cheng, Lei Ma, César Quilodrán Casas, Rossella Arcucci:
Med-UniC: Unifying Cross-Lingual Medical Vision-Language Pre-Training by Diminishing Bias. - A. Feder Cooper, Wentao Guo, Khiem Pham, Tiancheng Yuan, Charlie Ruan, Yucheng Lu, Christopher De Sa:
CD-GraB: Coordinating Distributed Example Orders for Provably Accelerated Training. - Stav Belogolovsky, Ido Greenberg, Danny Eytan, Shie Mannor:
Individualized Dosing Dynamics via Neural Eigen Decomposition. - Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. - Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang:
Counterfactual Generation with Identifiability Guarantees. - Jing Dong, Yuichi Yoshida:
A Batch-to-Online Transformation under Random-Order Model. - Yuxuan Ding, Chunna Tian, Haoxuan Ding, Lingqiao Liu:
The CLIP Model is Secretly an Image-to-Prompt Converter. - João B. S. Carvalho, Mengtao Zhang, Robin Geyer, Carlos Cotrini, Joachim M. Buhmann:
Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective. - Sasha Luccioni, Christopher Akiki, Margaret Mitchell, Yacine Jernite:
Stable Bias: Evaluating Societal Representations in Diffusion Models. - Indradyumna Roy, Rishi Agarwal, Soumen Chakrabarti, Anirban Dasgupta, Abir De:
Locality Sensitive Hashing in Fourier Frequency Domain For Soft Set Containment Search. - Julia Linhart, Alexandre Gramfort, Pedro Rodrigues:
L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference. - Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta:
Self-Supervised Reinforcement Learning that Transfers using Random Features. - Songhua Liu, Xinchao Wang:
MGDD: A Meta Generator for Fast Dataset Distillation. - Cornelius Brand, Robert Ganian, Mathis Rocton:
New Complexity-Theoretic Frontiers of Tractability for Neural Network Training. - Senzhang Wang, Jun Yin, Chaozhuo Li, Xing Xie, Jianxin Wang:
V-InFoR: A Robust Graph Neural Networks Explainer for Structurally Corrupted Graphs. - Alexandre Marthe, Aurélien Garivier, Claire Vernade:
Beyond Average Return in Markov Decision Processes. - Alberto Silvio Chiappa, Alessandro Marin Vargas, Ann Zixiang Huang, Alexander Mathis:
Latent exploration for Reinforcement Learning. - Tyler Kastner, Murat A. Erdogdu, Amir-massoud Farahmand:
Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning. - Christos Tsirigotis, João Monteiro, Pau Rodríguez, David Vázquez, Aaron C. Courville:
Group Robust Classification Without Any Group Information. - Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang:
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds. - Yingjie Liu, Xuan Liu, Hui Yu, Xuan Tang, Xian Wei:
Learning Dictionary for Visual Attention. - Enrico Giudice, Jack Kuipers, Giusi Moffa:
A Bayesian Take on Gaussian Process Networks. - Zaid Khan, Vijay Kumar B. G, Samuel Schulter, Manmohan Chandraker, Yun Fu:
Exploring Question Decomposition for Zero-Shot VQA. - Michael Feldman, David Donoho:
Sharp Recovery Thresholds of Tensor PCA Spectral Algorithms. - Zhilin Zhao, Longbing Cao:
R-divergence for Estimating Model-oriented Distribution Discrepancy. - Yufan Cai, Yun Lin, Chenyan Liu, Jinglian Wu, Yifan Zhang, Yiming Liu, Yeyun Gong, Jin Song Dong:
On-the-Fly Adapting Code Summarization on Trainable Cost-Effective Language Models. - Chudi Zhong, Zhi Chen, Jiachang Liu, Margo I. Seltzer, Cynthia Rudin:
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models. - Yipeng Li, Xinchen Lyu:
Convergence Analysis of Sequential Federated Learning on Heterogeneous Data. - Wei Tang, Weijia Zhang, Min-Ling Zhang:
Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning. - Osama A. Hanna, Lin Yang, Christina Fragouli:
Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination. - David Lüdke, Marin Bilos, Oleksandr Shchur, Marten Lienen, Stephan Günnemann:
Add and Thin: Diffusion for Temporal Point Processes. - Taehyun Cho, Seungyub Han, Heesoo Lee, Kyungjae Lee, Jungwoo Lee:
Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion. - Jinbiao Chen, Jiahai Wang, Zizhen Zhang, Zhiguang Cao, Te Ye, Siyuan Chen:
Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization. - Haotong Qin, Yulun Zhang, Yifu Ding, Yifan Liu, Xianglong Liu, Martin Danelljan, Fisher Yu:
QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution. - Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Mike Kirby, Shandian Zhe:
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition. - Chenyangguang Zhang, Yan Di, Ruida Zhang, Guangyao Zhai, Fabian Manhardt, Federico Tombari, Xiangyang Ji:
DDF-HO: Hand-Held Object Reconstruction via Conditional Directed Distance Field. - Minseon Kim, Hyeonjeong Ha, Sooel Son, Sung Ju Hwang:
Effective Targeted Attacks for Adversarial Self-Supervised Learning. - Sokhna Diarra Mbacke, Florence Clerc, Pascal Germain:
Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory. - Lucas Page-Caccia, Edoardo Maria Ponti, Zhan Su, Matheus Pereira, Nicolas Le Roux, Alessandro Sordoni:
Multi-Head Adapter Routing for Cross-Task Generalization. - Rui Peng, Xiaodong Gu, Luyang Tang, Shihe Shen, Fanqi Yu, Ronggang Wang:
GenS: Generalizable Neural Surface Reconstruction from Multi-View Images. - Jiarong Xu, Renhong Huang, Xin Jiang, Yuxuan Cao, Carl Yang, Chunping Wang, Yang Yang:
Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks. - Tahereh Toosi, Elias B. Issa:
Brain-like Flexible Visual Inference by Harnessing Feedback Feedforward Alignment. - Justin Lovelace, Varsha Kishore, Chao Wan, Eliot Shekhtman, Kilian Q. Weinberger:
Latent Diffusion for Language Generation. - Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet:
The emergence of clusters in self-attention dynamics. - Lingxiao Li, Samuel Hurault, Justin M. Solomon:
Self-Consistent Velocity Matching of Probability Flows. - Tianrong Chen, Guan-Horng Liu, Molei Tao, Evangelos A. Theodorou:
Deep Momentum Multi-Marginal Schrödinger Bridge. - Weihang Dai, Yao Du, Hanru Bai, Kwang-Ting Cheng, Xiaomeng Li:
Semi-Supervised Contrastive Learning for Deep Regression with Ordinal Rankings from Spectral Seriation. - Yi Wu, Ziqiang Li, Chaoyue Wang, Heliang Zheng, Shanshan Zhao, Bin Li, Dacheng Tao:
Domain Re-Modulation for Few-Shot Generative Domain Adaptation. - Yu Bai, Fan Chen, Huan Wang, Caiming Xiong, Song Mei:
Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection. - Yulun Zhang, Matthew C. Fontaine, Varun Bhatt, Stefanos Nikolaidis, Jiaoyang Li:
Arbitrarily Scalable Environment Generators via Neural Cellular Automata. - Bo Liu, Yihao Feng, Peter Stone, Qiang Liu:
FAMO: Fast Adaptive Multitask Optimization. - Zhou Lu:
A Theory of Multimodal Learning. - Haixin Wang, Hao Wu, Jinan Sun, Shikun Zhang, Chong Chen, Xian-Sheng Hua, Xiao Luo:
IDEA: An Invariant Perspective for Efficient Domain Adaptive Image Retrieval. - Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel:
Learning Provably Robust Estimators for Inverse Problems via Jittering. - Rajat Modi, Vibhav Vineet, Yogesh S. Rawat:
On Occlusions in Video Action Detection: Benchmark Datasets And Training Recipes. - Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Jin Sun, Ninghao Liu:
Black-box Backdoor Defense via Zero-shot Image Purification. - Arvind V. Mahankali, Haochen Zhang, Kefan Dong, Margalit Glasgow, Tengyu Ma:
Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time. - Zhejun Zhang, Alexander Liniger, Christos Sakaridis, Fisher Yu, Luc Van Gool:
Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding. - Zhiheng Liu, Yifei Zhang, Yujun Shen, Kecheng Zheng, Kai Zhu, Ruili Feng, Yu Liu, Deli Zhao, Jingren Zhou, Yang Cao:
Customizable Image Synthesis with Multiple Subjects. - Chen Zeno, Greg Ongie, Yaniv Blumenfeld, Nir Weinberger, Daniel Soudry:
How do Minimum-Norm Shallow Denoisers Look in Function Space? - Feng Zhang, Ming Tian, Zhiqiang Li, Bin Xu, Qingbo Lu, Changxin Gao, Nong Sang:
Lookup Table meets Local Laplacian Filter: Pyramid Reconstruction Network for Tone Mapping. - Guoxi Huang, Hongtao Fu, Adrian G. Bors:
Masked Image Residual Learning for Scaling Deeper Vision Transformers. - Arun Jambulapati, Kevin Tian:
Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations. - Míriam Barrabés, Daniel Mas Montserrat, Margarita Geleta, Xavier Giró-i-Nieto, Alexander G. Ioannidis:
Adversarial Learning for Feature Shift Detection and Correction. - Lingwei Zhu, Zheng Chen, Matthew Schlegel, Martha White:
General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence. - Jianing Li, Vardan Papyan:
Residual Alignment: Uncovering the Mechanisms of Residual Networks. - Takashi Furuya, Michael Puthawala, Matti Lassas, Maarten V. de Hoop:
Globally injective and bijective neural operators. - Rahul Mazumder, Haoyue Wang:
On the Convergence of CART under Sufficient Impurity Decrease Condition. - Ali TehraniJamsaz, Quazi Ishtiaque Mahmud, Le Chen, Nesreen K. Ahmed, Ali Jannesari:
PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis. - Etienne Boursier, Nicolas Flammarion:
Penalising the biases in norm regularisation enforces sparsity. - SeungHwan An, Jong-June Jeon:
Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation. - Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue, Hado Philip van Hasselt, András György, Satinder Singh:
Optimistic Meta-Gradients. - Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik:
Norm-guided latent space exploration for text-to-image generation. - Roland S. Zimmermann, Thomas Klein, Wieland Brendel:
Scale Alone Does not Improve Mechanistic Interpretability in Vision Models. - Mirac Suzgun, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers, Stuart M. Shieber:
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications. - Junho Song, Keonwoo Kim, Jeonglyul Oh, Sungzoon Cho:
MEMTO: Memory-guided Transformer for Multivariate Time Series Anomaly Detection. - Bonwoo Lee, Jeongyoun Ahn, Cheolwoo Park:
Minimax Risks and Optimal Procedures for Estimation under Functional Local Differential Privacy. - Hyun Dong Lee, Andrew Warrington, Joshua I. Glaser, Scott W. Linderman:
Switching Autoregressive Low-rank Tensor Models. - Guy Kornowski, Gilad Yehudai, Ohad Shamir:
From Tempered to Benign Overfitting in ReLU Neural Networks. - Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein:
Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images. - Soheil Hor, Shubo Yang, Jaeho Choi, Amin Arbabian:
MVDoppler: Unleashing the Power of Multi-View Doppler for MicroMotion-based Gait Classification. - Yian Deng, Tingting Mu:
Understanding and Improving Ensemble Adversarial Defense. - Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann:
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions. - Emily Silcock, Abhishek Arora, Melissa Dell:
A Massive Scale Semantic Similarity Dataset of Historical English. - Alessandro Sordoni, Eric Yuan, Marc-Alexandre Côté, Matheus Pereira, Adam Trischler, Ziang Xiao, Arian Hosseini, Friederike Niedtner, Nicolas Le Roux:
Joint Prompt Optimization of Stacked LLMs using Variational Inference. - Yufeng Zhang, Jialu Pan, Li Ken Li, Wanwei Liu, Zhenbang Chen, Xinwang Liu, Ji Wang:
On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions. - Bochen Lyu, Zhanxing Zhu:
Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network. - Haotian Sun, Yuchen Zhuang, Lingkai Kong, Bo Dai, Chao Zhang:
AdaPlanner: Adaptive Planning from Feedback with Language Models. - Loukas Kavouras, Konstantinos Tsopelas, Giorgos Giannopoulos, Dimitris Sacharidis, Eleni Psaroudaki, Nikolaos Theologitis, Dimitrios Rontogiannis, Dimitris Fotakis, Ioannis Z. Emiris:
Fairness Aware Counterfactuals for Subgroups. - Tim Kucera, Carlos G. Oliver, Dexiong Chen, Karsten M. Borgwardt:
ProteinShake: Building datasets and benchmarks for deep learning on protein structures. - Ziheng Sun, Chris Ding, Jicong Fan:
Lovász Principle for Unsupervised Graph Representation Learning. - Chenyang Le, Yao Qian, Long Zhou, Shujie Liu, Yanmin Qian, Michael Zeng, Xuedong Huang:
ComSL: A Composite Speech-Language Model for End-to-End Speech-to-Text Translation. - Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun:
Reverse Engineering Self-Supervised Learning. - Alexander H. Liu, Heng-Jui Chang, Michael Auli, Wei-Ning Hsu, James R. Glass:
DinoSR: Self-Distillation and Online Clustering for Self-supervised Speech Representation Learning. - David Mizrahi, Roman Bachmann, Oguzhan Fatih Kar, Teresa Yeo, Mingfei Gao, Afshin Dehghan, Amir Zamir:
4M: Massively Multimodal Masked Modeling. - Puhua Jiang, Mingze Sun, Ruqi Huang:
Non-Rigid Shape Registration via Deep Functional Maps Prior. - Ti-Rong Wu, Hung Guei, Ting-Han Wei, Chung-Chin Shih, Jui-Te Chin, I-Chen Wu:
Game Solving with Online Fine-Tuning. - Jia-Qi Yang, De-Chuan Zhan, Le Gan:
Beyond probability partitions: Calibrating neural networks with semantic aware grouping. - Qi Zhang, Yifei Wang, Yisen Wang:
Identifiable Contrastive Learning with Automatic Feature Importance Discovery. - Lifan Yuan, Yangyi Chen, Ganqu Cui, Hongcheng Gao, Fangyuan Zou, Xingyi Cheng, Heng Ji, Zhiyuan Liu, Maosong Sun:
Revisiting Out-of-distribution Robustness in NLP: Benchmarks, Analysis, and LLMs Evaluations. - Zicheng Zhang, Bonan Li, Xuecheng Nie, Congying Han, Tiande Guo, Luoqi Liu:
Towards Consistent Video Editing with Text-to-Image Diffusion Models. - Dong Qiao, Chris Ding, Jicong Fan:
Federated Spectral Clustering via Secure Similarity Reconstruction. - Yexiong Lin, Yu Yao, Xiaolong Shi, Mingming Gong, Xu Shen, Dong Xu, Tongliang Liu:
CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation. - Felipe Maia Polo, Yuekai Sun, Moulinath Banerjee:
Conditional independence testing under misspecified inductive biases. - Yang Deng, Weibin Wu, Jianping Zhang, Zibin Zheng:
Blurred-Dilated Method for Adversarial Attacks. - Jianhong Bai, Zuozhu Liu, Hualiang Wang, Ruizhe Chen, Lianrui Mu, Xiaomeng Li, Joey Tianyi Zhou, Yang Feng, Jian Wu, Haoji Hu:
Towards Distribution-Agnostic Generalized Category Discovery. - Chengbin Du, Yanxi Li, Zhongwei Qiu, Chang Xu:
Stable Diffusion is Unstable. - Yihan Zhou, Eric Price:
A Competitive Algorithm for Agnostic Active Learning. - Zhenqian Shen, Hansi Yang, Yong Li, James T. Kwok, Quanming Yao:
Efficient Hyper-parameter Optimization with Cubic Regularization. - Duo Peng, Li Xu, Qiuhong Ke, Ping Hu, Jun Liu:
Joint Attribute and Model Generalization Learning for Privacy-Preserving Action Recognition. - Xingrui Wang, Wufei Ma, Zhuowan Li, Adam Kortylewski, Alan L. Yuille:
3D-Aware Visual Question Answering about Parts, Poses and Occlusions. - Yutao Cui, Tianhui Song, Gangshan Wu, Limin Wang:
MixFormerV2: Efficient Fully Transformer Tracking. - Weitian Huang, Sirui Yang, Hongmin Cai:
Generalized Information-theoretic Multi-view Clustering. - Martin Saveski, Steven Jecmen, Nihar B. Shah, Johan Ugander:
Counterfactual Evaluation of Peer-Review Assignment Policies. - Çaglar Hizli, St John, Anne Juuti, Tuure Saarinen, Kirsi Pietiläinen, Pekka Marttinen:
Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions. - Hannaneh Akrami, Kurt Mehlhorn, Masoud Seddighin, Golnoosh Shahkarami:
Randomized and Deterministic Maximin-share Approximations for Fractionally Subadditive Valuations. - Adrián Javaloy, Pablo Sánchez-Martín, Isabel Valera:
Causal normalizing flows: from theory to practice. - Masoud Moravej Khorasani, Erik Weyer:
Maximum Average Randomly Sampled: A Scale Free and Non-parametric Algorithm for Stochastic Bandits. - Bowen Tan, Yun Zhu, Lijuan Liu, Eric P. Xing, Zhiting Hu, Jindong Chen:
Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer. - Qi Xu, Yuyuan Gao, Jiangrong Shen, Yaxin Li, Xuming Ran, Huajin Tang, Gang Pan:
Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks. - Qihang Fang, Yafei Song, Keqiang Li, Liefeng Bo:
Reducing Shape-Radiance Ambiguity in Radiance Fields with a Closed-Form Color Estimation Method. - Kevin Clark, Priyank Jaini:
Text-to-Image Diffusion Models are Zero Shot Classifiers. - Aveen Dayal, Vimal K. B., Linga Reddy Cenkeramaddi, C. Krishna Mohan, Abhinav Kumar, Vineeth N. Balasubramanian:
MADG: Margin-based Adversarial Learning for Domain Generalization. - Cassidy Laidlaw, Stuart J. Russell, Anca D. Dragan:
Bridging RL Theory and Practice with the Effective Horizon. - Zeqiu Wu, Yushi Hu, Weijia Shi, Nouha Dziri, Alane Suhr, Prithviraj Ammanabrolu, Noah A. Smith, Mari Ostendorf, Hannaneh Hajishirzi:
Fine-Grained Human Feedback Gives Better Rewards for Language Model Training. - Rajat Vadiraj Dwaraknath, Ishani Karmarkar, Aaron Sidford:
Towards Optimal Effective Resistance Estimation. - Shuo Sun, Molei Qin, Wentao Zhang, Haochong Xia, Chuqiao Zong, Jie Ying, Yonggang Xie, Lingxuan Zhao, Xinrun Wang, Bo An:
TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning. - Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark W. Barrett, Michael I. Jordan, Jiantao Jiao:
Towards Optimal Caching and Model Selection for Large Model Inference. - Yue Li, Yueyi Zhang, Juntian Ye, Feihu Xu, Zhiwei Xiong:
Deep Non-line-of-sight Imaging from Under-scanning Measurements. - Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li:
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback. - Jiaming Gu, Minchao Jiang, Hongsheng Li, Xiaoyuan Lu, Guangming Zhu, Syed Afaq Ali Shah, Liang Zhang, Mohammed Bennamoun:
UE4-NeRF: Neural Radiance Field for Real-Time Rendering of Large-Scale Scene. - Yi Yu, Xue Yang, Qingyun Li, Yue Zhou, Feipeng Da, Junchi Yan:
H2RBox-v2: Incorporating Symmetry for Boosting Horizontal Box Supervised Oriented Object Detection. - Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nicholas Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Yang, Shimon Whiteson, Brandyn White, Dragomir Anguelov:
The Waymo Open Sim Agents Challenge. - Gellért Weisz, András György, Csaba Szepesvári:
Online RL in Linearly qπ-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore. - Laura Fee Nern, Harsh Raj, Maurice André Georgi, Yash Sharma:
On Transfer of Adversarial Robustness from Pretraining to Downstream Tasks. - Zebang Shen, Zhenfu Wang:
Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs. - Zhiyu Lin, Yifei Gao, Yunfan Yang, Jitao Sang:
Revisiting Visual Model Robustness: A Frequency Long-Tailed Distribution View. - Hai Zhang, Hang Yu, Junqiao Zhao, Di Zhang, Xiao Zhang, Hongtu Zhou, Chang Huang, Chen Ye:
How to Fine-tune the Model: Unified Model Shift and Model Bias Policy Optimization. - Shipra Agrawal, Yiding Feng, Wei Tang:
Dynamic Pricing and Learning with Bayesian Persuasion. - Hongting Ye, Yalu Zheng, Yueying Li, Ke Zhang, Youyong Kong, Yonggui Yuan:
RH-BrainFS: Regional Heterogeneous Multimodal Brain Networks Fusion Strategy. - Fuzhao Xue, Yao Fu, Wangchunshu Zhou, Zangwei Zheng, Yang You:
To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis. - Zhaocheng Zhu, Xinyu Yuan, Michael Galkin, Louis-Pascal A. C. Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang:
A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs. - Shengcao Cao, Dhiraj Joshi, Liangyan Gui, Yu-Xiong Wang:
HASSOD: Hierarchical Adaptive Self-Supervised Object Detection. - Luke Taylor, Andrew King, Nicol S. Harper:
Addressing the speed-accuracy simulation trade-off for adaptive spiking neurons. - Tingting Dan, Jiaqi Ding, Ziquan Wei, Shahar Z. Kovalsky, Minjeong Kim, Won Hwa Kim, Guorong Wu:
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals. - Raymond Feng, Flávio Calmon, Hao Wang:
Adapting Fairness Interventions to Missing Values. - Christopher Subia-Waud, Srinandan Dasmahapatra:
Probabilistic Weight Fixing: Large-scale training of neural network weight uncertainties for quantisation. - Ian Char, Jeff Schneider:
PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks. - Christopher Yeh, Victor Li, Rajeev Datta, Julio Arroyo, Nicolas Christianson, Chi Zhang, Yize Chen, Mohammad Mehdi Hosseini, Azarang Golmohammadi, Yuanyuan Shi, Yisong Yue, Adam Wierman:
SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems. - Navdeep Kumar, Esther Derman, Matthieu Geist, Kfir Y. Levy, Shie Mannor:
Policy Gradient for Rectangular Robust Markov Decision Processes. - Marco Bellagente, Manuel Brack, Hannah Teufel, Felix Friedrich, Björn Deiseroth, Constantin Eichenberg, Andrew Dai, Robert Baldock, Souradeep Nanda, Koen Oostermeijer, Andrés Felipe Cruz-Salinas, Patrick Schramowski, Kristian Kersting, Samuel Weinbach:
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation. - Jiayuan Mao, Tomás Lozano-Pérez, Joshua B. Tenenbaum, Leslie Pack Kaelbling:
What Planning Problems Can A Relational Neural Network Solve? - Matthias Gerstgrasser, Tom Danino, Sarah Keren:
Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning. - Hua Yuan, Yu Shi, Ning Xu, Xu Yang, Xin Geng, Yong Rui:
Learning From Biased Soft Labels. - Bohan Zhou, Ke Li, Jiechuan Jiang, Zongqing Lu:
Learning from Visual Observation via Offline Pretrained State-to-Go Transformer. - Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling:
Rotating Features for Object Discovery. - Wenlong Huang, Fei Xia, Dhruv Shah, Danny Driess, Andy Zeng, Yao Lu, Pete Florence, Igor Mordatch, Sergey Levine, Karol Hausman, Brian Ichter:
Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents. - Taicheng Guo, Kehan Guo, Bozhao Nan, Zhenwen Liang, Zhichun Guo, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang:
What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks. - Haoqing Wang, Shibo Jie, Zhihong Deng:
Focus Your Attention when Few-Shot Classification. - Christopher Rawles, Alice Li, Daniel Rodriguez, Oriana Riva, Timothy P. Lillicrap:
AndroidInTheWild: A Large-Scale Dataset For Android Device Control. - Jean-Yves Franceschi, Mike Gartrell, Ludovic Dos Santos, Thibaut Issenhuth, Emmanuel de Bézenac, Mickaël Chen, Alain Rakotomamonjy:
Unifying GANs and Score-Based Diffusion as Generative Particle Models. - Tolga Ergen, Mert Pilanci:
Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks. - Adam J. Stewart, Nils Lehmann, Isaac A. Corley, Yi Wang, Yi-Chia Chang, Nassim Ait Ali Braham, Shradha Sehgal, Caleb Robinson, Arindam Banerjee:
SSL4EO-L: Datasets and Foundation Models for Landsat Imagery. - Matteo Pagliardini, Daniele Paliotta, Martin Jaggi, François Fleuret:
Fast Attention Over Long Sequences With Dynamic Sparse Flash Attention. - Guozheng Ma, Linrui Zhang, Haoyu Wang, Lu Li, Zilin Wang, Zhen Wang, Li Shen, Xueqian Wang, Dacheng Tao:
Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning. - Han Hu, Haolan Zhan, Yujin Huang, Di Liu:
Pairwise GUI Dataset Construction Between Android Phones and Tablets. - Guangchen Lan, Han Wang, James Anderson, Christopher G. Brinton, Vaneet Aggarwal:
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates. - Leon Klein, Andreas Krämer, Frank Noé:
Equivariant flow matching. - Jiawei Ren, Mingyuan Zhang, Cunjun Yu, Xiao Ma, Liang Pan, Ziwei Liu:
InsActor: Instruction-driven Physics-based Characters. - Diego Martinez-Taboada, Aaditya Ramdas, Edward Kennedy:
An Efficient Doubly-Robust Test for the Kernel Treatment Effect. - Ruiqi Zhang, Andrea Zanette:
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data. - Fivos Kalogiannis, Ioannis Panageas:
Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria. - Sirui Li, Wenbin Ouyang, Max B. Paulus, Cathy Wu:
Learning to Configure Separators in Branch-and-Cut. - Alex Foo, Wynne Hsu, Mong-Li Lee:
Multi-Object Representation Learning via Feature Connectivity and Object-Centric Regularization. - Huiqiao Fu, Kaiqiang Tang, Yuanyang Lu, Yiming Qi, Guizhou Deng, Flood Sung, Chunlin Chen:
Ess-InfoGAIL: Semi-supervised Imitation Learning from Imbalanced Demonstrations. - Ming Xu, Timothy L. Molloy, Stephen Gould:
Revisiting Implicit Differentiation for Learning Problems in Optimal Control. - Yesom Park, Taekyung Lee, Jooyoung Hahn, Myungjoo Kang:
p-Poisson surface reconstruction in curl-free flow from point clouds. - Yichi Zhang, Ankush Garg, Yuan Cao, Lukasz Lew, Behrooz Ghorbani, Zhiru Zhang, Orhan Firat:
Binarized Neural Machine Translation. - Nived Rajaraman, Devvrit, Aryan Mokhtari, Kannan Ramchandran:
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing. - Tushar Nagarajan, Santhosh Kumar Ramakrishnan, Ruta Desai, James Hillis, Kristen Grauman:
EgoEnv: Human-centric environment representations from egocentric video. - Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip H. S. Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko:
Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union. - Ashwinkumar Badanidiyuru Varadaraja, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang:
Optimal Unbiased Randomizers for Regression with Label Differential Privacy. - Yang Yue, Rui Lu, Bingyi Kang, Shiji Song, Gao Huang:
Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL. - Samuel McCauley, Benjamin Moseley, Aidin Niaparast, Shikha Singh:
Online List Labeling with Predictions. - Lorenzo Giambagli, Lorenzo Buffoni, Lorenzo Chicchi, Duccio Fanelli:
How a Student becomes a Teacher: learning and forgetting through Spectral methods. - Yanshu Zhang, Shichong Peng, Alireza Moazeni, Ke Li:
PAPR: Proximity Attention Point Rendering. - Jintong Gao, He Zhao, Zhuo Li, Dandan Guo:
Enhancing Minority Classes by Mixing: An Adaptative Optimal Transport Approach for Long-tailed Classification. - Weida Li, Yaoliang Yu:
Robust Data Valuation with Weighted Banzhaf Values. - Guanren Qiao, Guiliang Liu, Pascal Poupart, Zhiqiang Xu:
Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations. - Zhiqin Yang, Yonggang Zhang, Yu Zheng, Xinmei Tian, Hao Peng, Tongliang Liu, Bo Han:
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning. - Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, Prateek Mittal:
A Privacy-Friendly Approach to Data Valuation. - Yibo Jiang, Bryon Aragam:
Learning Nonparametric Latent Causal Graphs with Unknown Interventions. - Hao Qin, Kwang-Sung Jun, Chicheng Zhang:
Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards. - Artyom Gadetsky, Maria Brbic:
The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning. - Yi Ren, Samuel Lavoie, Michael Galkin, Danica J. Sutherland, Aaron C. Courville:
Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings. - Haixiang Zhang, Ying Chen, Javad Lavaei:
Geometric Analysis of Matrix Sensing over Graphs. - Phillip Pope, David Jacobs:
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach. - Hui Yuan, Kaixuan Huang, Chengzhuo Ni, Minshuo Chen, Mengdi Wang:
Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement. - Luning Sun, Xu Han, Han Gao, Jian-Xun Wang, Liping Liu:
Unifying Predictions of Deterministic and Stochastic Physics in Mesh-reduced Space with Sequential Flow Generative Model. - Abhra Chaudhuri, Massimiliano Mancini, Zeynep Akata, Anjan Dutta:
Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships. - Long-Fei Li, Peng Zhao, Zhi-Hua Zhou:
Dynamic Regret of Adversarial Linear Mixture MDPs. - Marina Munkhoeva, Ivan V. Oseledets:
Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning. - Zhangsihao Yang, Mengwei Ren, Kaize Ding, Guido Gerig, Yalin Wang:
Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation. - Chaoyue Liu, Dmitriy Drusvyatskiy, Misha Belkin, Damek Davis, Yi-An Ma:
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems. - Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Sanjiv Kumar:
ResMem: Learn what you can and memorize the rest. - Jiachen Liang, Ruibing Hou, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin Chen:
Generalized Semi-Supervised Learning via Self-Supervised Feature Adaptation. - Jaron Maene, Luc De Raedt:
Soft-Unification in Deep Probabilistic Logic. - Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann:
Scaling MLPs: A Tale of Inductive Bias. - Guillaume Wang, Lénaïc Chizat:
Local Convergence of Gradient Methods for Min-Max Games: Partial Curvature Generically Suffices. - Zhanpeng Zhou, Yongyi Yang, Xiaojiang Yang, Junchi Yan, Wei Hu:
Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity. - Xuefeng Du, Yiyou Sun, Jerry Zhu, Yixuan Li:
Dream the Impossible: Outlier Imagination with Diffusion Models. - Elie Bursztein, Marina Zhang, Owen Vallis, Xinyu Jia, Alexey Kurakin:
RETVec: Resilient and Efficient Text Vectorizer. - Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan:
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. - Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Do Not Marginalize Mechanisms, Rather Consolidate! - Ruihai Wu, Kai Cheng, Yan Zhao, Chuanruo Ning, Guanqi Zhan, Hao Dong:
Learning Environment-Aware Affordance for 3D Articulated Object Manipulation under Occlusions. - Cristina Menghini, Andrew Delworth, Stephen H. Bach:
Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning. - Yangqing Fu, Ming Sun, Buqing Nie, Yue Gao:
Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction. - Tangyu Jiang, Haodi Wang, Rongfang Bie:
MeCo: Zero-Shot NAS with One Data and Single Forward Pass via Minimum Eigenvalue of Correlation. - Andrea Coletta, Sriram Gopalakrishnan, Daniel Borrajo, Svitlana Vyetrenko:
On the Constrained Time-Series Generation Problem. - Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao:
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. - Alaa Maalouf, Murad Tukan, Noel Loo, Ramin M. Hasani, Mathias Lechner, Daniela Rus:
On the Size and Approximation Error of Distilled Datasets. - Mohammad Pedramfar, Christopher J. Quinn, Vaneet Aggarwal:
A Unified Approach for Maximizing Continuous DR-submodular Functions. - Thanh Nguyen-Tang, Raman Arora:
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond. - Shibal Ibrahim, Gabriel Afriat, Kayhan Behdin, Rahul Mazumder:
GRAND-SLAMIN' Interpretable Additive Modeling with Structural Constraints. - Sangwoo Mo, Minkyu Kim, Kyungmin Lee, Jinwoo Shin:
S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions. - Hangfan Zhang, Jinyuan Jia, Jinghui Chen, Lu Lin, Dinghao Wu:
A3FL: Adversarially Adaptive Backdoor Attacks to Federated Learning. - Tianle Liu, Promit Ghosal, Krishnakumar Balasubramanian, Natesh S. Pillai:
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent. - Lothar D. Narins, Andrew T. Scott, Aakash Gautam, Anagha Kulkarni, Mar Castanon, Benjamin Kao, Shasta Ihorn, Yue-Ting Siu, James M. Mason, Alexander Blum, Ilmi Yoon:
Validated Image Caption Rating Dataset. - Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski:
Provable benefits of score matching. - Yankun Huang, Qihang Lin:
Oracle Complexity of Single-Loop Switching Subgradient Methods for Non-Smooth Weakly Convex Functional Constrained Optimization. - Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu, Ruoxi Jia:
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources. - Jonathan Schmidt, Philipp Hennig, Jörg Nick, Filip Tronarp:
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions. - Kevin J. Miller, Maria K. Eckstein, Matt M. Botvinick, Zeb Kurth-Nelson:
Cognitive Model Discovery via Disentangled RNNs. - Dan Qiao, Yu-Xiang Wang:
Offline Reinforcement Learning with Differential Privacy. - Matan Levy, Rami Ben-Ari, Nir Darshan, Dani Lischinski:
Chatting Makes Perfect: Chat-based Image Retrieval. - Junhoo Lee, Jayeon Yoo, Nojun Kwak:
SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning. - Jiahua Dong, Yu-Xiong Wang:
ViCA-NeRF: View-Consistency-Aware 3D Editing of Neural Radiance Fields. - Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Pang Wei Koh, Daphne Ippolito, Florian Tramèr, Ludwig Schmidt:
Are aligned neural networks adversarially aligned? - Wenhai Wang, Zhe Chen, Xiaokang Chen, Jiannan Wu, Xizhou Zhu, Gang Zeng, Ping Luo, Tong Lu, Jie Zhou, Yu Qiao, Jifeng Dai:
VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks. - Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius:
Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities. - Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo:
Regret Matching+: (In)Stability and Fast Convergence in Games. - Scott Fujimoto, Wei-Di Chang, Edward J. Smith, Shixiang Gu, Doina Precup, David Meger:
For SALE: State-Action Representation Learning for Deep Reinforcement Learning. - Julia Olkhovskaya, Jack J. Mayo, Tim van Erven, Gergely Neu, Chen-Yu Wei:
First- and Second-Order Bounds for Adversarial Linear Contextual Bandits. - Nika Haghtalab, Chara Podimata, Kunhe Yang:
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents. - Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun, Gyoung S. Na, Chanyoung Park:
Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer. - Yuanyuan Liu, Fanhua Shang, Weixin An, Junhao Liu, Hongying Liu, Zhouchen Lin:
A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization. - Yu Liang, Shiliang Zhang, Li Ken Li, Xiaoyu Wang:
Unleashing the Full Potential of Product Quantization for Large-Scale Image Retrieval. - Shay Moran, Hilla Schefler, Jonathan Shafer:
The Bayesian Stability Zoo. - Le Yang, Siyang Gao, Chin Pang Ho:
Improving the Knowledge Gradient Algorithm. - Mingyu Yang, Yaodong Yang, Zhenbo Lu, Wengang Zhou, Houqiang Li:
Hierarchical Multi-Agent Skill Discovery. - Theo Adrai, Guy Ohayon, Michael Elad, Tomer Michaeli:
Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restoration. - Rui Sun, Huayu Mai, Tianzhu Zhang, Feng Wu:
DAW: Exploring the Better Weighting Function for Semi-supervised Semantic Segmentation. - Alex Tamkin, Margalit Glasgow, Xiluo He, Noah D. Goodman:
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning. - Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao, Tom Goldstein:
On the Exploitability of Instruction Tuning. - Chenran Li, Chen Tang, Haruki Nishimura, Jean Mercat, Masayoshi Tomizuka, Wei Zhan:
Residual Q-Learning: Offline and Online Policy Customization without Value. - Yiming Lei, Zilong Li, Yangyang Li, Junping Zhang, Hongming Shan:
LICO: Explainable Models with Language-Image COnsistency. - Benjamin J. Holzschuh, Simona Vegetti, Nils Thuerey:
Solving Inverse Physics Problems with Score Matching. - Shashanka Venkataramanan, Ewa Kijak, Laurent Amsaleg, Yannis Avrithis:
Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples. - Mircea Petrache, Shubhendu Trivedi:
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance. - Chaoran Cheng, Jian Peng:
Equivariant Neural Operator Learning with Graphon Convolution. - Tankred Saanum, Noémi Élteto, Peter Dayan, Marcel Binz, Eric Schulz:
Reinforcement Learning with Simple Sequence Priors. - Zhiyuan Zhang, Deli Chen, Hao Zhou, Fandong Meng, Jie Zhou, Xu Sun:
Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense. - Shaochen (Henry) Zhong, Zaichuan You, Jiamu Zhang, Sebastian Zhao, Zachary LeClaire, Zirui Liu, Daochen Zha, Vipin Chaudhary, Shuai Xu, Xia Hu:
One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning. - Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng:
Survival Instinct in Offline Reinforcement Learning. - Jacob Beck, Risto Vuorio, Zheng Xiong, Shimon Whiteson:
Recurrent Hypernetworks are Surprisingly Strong in Meta-RL. - Edith Cohen, Xin Lyu:
The Target-Charging Technique for Privacy Analysis across Interactive Computations. - Guangrong Zhao, Yurun Yang, Jingwei Liu, Ning Chen, Yiran Shen, Hongkai Wen, Guohao Lan:
EV-Eye: Rethinking High-frequency Eye Tracking through the Lenses of Event Cameras. - Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet:
Diffusion Schrödinger Bridge Matching. - Ruoyu Li, Qing Li, Yu Zhang, Dan Zhao, Yong Jiang, Yong Yang:
Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction. - Mitsuhiko Nakamoto, Simon Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine:
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning. - Hojoon Lee, Hanseul Cho, Hyunseung Kim, Daehoon Gwak, Joonkee Kim, Jaegul Choo, Se-Young Yun, Chulhee Yun:
PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning. - Nic Fishman, Leo Klarner, Emile Mathieu, Michael J. Hutchinson, Valentin De Bortoli:
Metropolis Sampling for Constrained Diffusion Models. - Yixun Liang, Hao He, Yingcong Chen:
ReTR: Modeling Rendering Via Transformer for Generalizable Neural Surface Reconstruction. - Yuanxin Liu, Lei Li, Shuhuai Ren, Rundong Gao, Shicheng Li, Sishuo Chen, Xu Sun, Lu Hou:
FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation. - Anton Xue, Rajeev Alur, Eric Wong:
Stability Guarantees for Feature Attributions with Multiplicative Smoothing. - Andrey Kuzmin, Markus Nagel, Mart van Baalen, Arash Behboodi, Tijmen Blankevoort:
Pruning vs Quantization: Which is Better? - Mohammad Mahdi Rahimi, Hasnain Irshad Bhatti, Younghyun Park, Humaira Kousar, Do-Yeon Kim, Jaekyun Moon:
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning. - Yansong Ning, Hao Liu, Hao Wang, Zhenyu Zeng, Hui Xiong:
UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction. - Zelei Cheng, Xian Wu, Jiahao Yu, Wenhai Sun, Wenbo Guo, Xinyu Xing:
StateMask: Explaining Deep Reinforcement Learning through State Mask. - Guanghui Wang, Zihao Hu, Vidya Muthukumar, Jacob D. Abernethy:
Faster Margin Maximization Rates for Generic Optimization Methods. - Zichen Vincent Zhang, Johannes Kirschner, Junxi Zhang, Francesco Zanini, Alex Ayoub, Masood Dehghan, Dale Schuurmans:
Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off. - Li Fan, Ruida Zhou, Chao Tian, Cong Shen:
Federated Linear Bandits with Finite Adversarial Actions. - Zachary Coalson, Gabriel Ritter, Rakesh Bobba, Sanghyun Hong:
BERT Lost Patience Won't Be Robust to Adversarial Slowdown. - Zeming Chen, Gail Weiss, Eric Mitchell, Asli Celikyilmaz, Antoine Bosselut:
RECKONING: Reasoning through Dynamic Knowledge Encoding. - Cansu Sancaktar, Justus H. Piater, Georg Martius:
Regularity as Intrinsic Reward for Free Play. - Zekun Li, Baolin Peng, Pengcheng He, Michel Galley, Jianfeng Gao, Xifeng Yan:
Guiding Large Language Models via Directional Stimulus Prompting. - Hitesh Sapkota, Dingrong Wang, Zhiqiang Tao, Qi Yu:
Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training. - Junfeng Zuo, Xiao Liu, Ying Nian Wu, Si Wu, Wenhao Zhang:
A Recurrent Neural Circuit Mechanism of Temporal-scaling Equivariant Representation. - Arnaud Robert, Ciara Pike-Burke, Aldo A. Faisal:
Sample Complexity of Goal-Conditioned Hierarchical Reinforcement Learning. - Han Cui, Shu Zhong, Jiacheng Wu, Zichao Shen, Naim Dahnoun, Yiren Zhao:
MiliPoint: A Point Cloud Dataset for mmWave Radar. - Yun Yi, Haokui Zhang, Rong Xiao, Nannan Wang, Xiaoyu Wang:
NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning. - Lalit Manam, Venu Madhav Govindu:
Sensitivity in Translation Averaging. - Chung-En Tsai, Ying-Ting Lin, Yen-Huan Li:
Data-Dependent Bounds for Online Portfolio Selection Without Lipschitzness and Smoothness. - Sloan Nietert, Ziv Goldfeld, Soroosh Shafiee:
Outlier-Robust Wasserstein DRO. - Jiaqi Liu, Jian Lou, Zhan Qin, Kui Ren:
Certified Minimax Unlearning with Generalization Rates and Deletion Capacity. - Haoran Yang, Xiangyu Zhao, Yicong Li, Hongxu Chen, Guandong Xu:
An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations. - Swarnadeep Saha, Peter Hase, Mohit Bansal:
Can Language Models Teach? Teacher Explanations Improve Student Performance via Personalization. - Wenhan Xian, Heng Huang:
Finding Local Minima Efficiently in Decentralized Optimization. - David Ruhe, Johannes Brandstetter, Patrick Forré:
Clifford Group Equivariant Neural Networks. - Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, Junlei Zhang, Jinghan Zhang, Tangjun Su, Junteng Liu, Chuancheng Lv, Yikai Zhang, Jiayi Lei, Yao Fu, Maosong Sun, Junxian He:
C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models. - Stefan Lionar, Xiangyu Xu, Min Lin, Gim Hee Lee:
NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF. - Jungbin Kim, Insoon Yang:
Convergence analysis of ODE models for accelerated first-order methods via positive semidefinite kernels. - Joshua Southern, Jeremy Wayland, Michael M. Bronstein, Bastian Rieck:
Curvature Filtrations for Graph Generative Model Evaluation. - Haoxing Chen, Zhuoer Xu, Zhangxuan Gu, Jun Lan, Xing Zheng, Yaohui Li, Changhua Meng, Huijia Zhu, Weiqiang Wang:
DiffUTE: Universal Text Editing Diffusion Model. - Erik Lien Bolager, Iryna Burak, Chinmay Datar, Qing Sun, Felix Dietrich:
Sampling weights of deep neural networks. - Josh Alman, Zhao Song:
Fast Attention Requires Bounded Entries. - Tingliang Feng, Hao Shi, Xueyang Liu, Wei Feng, Liang Wan, Yanlin Zhou, Di Lin:
Open Compound Domain Adaptation with Object Style Compensation for Semantic Segmentation. - Johanna Immonen, Amauri H. Souza, Vikas Garg:
Going beyond persistent homology using persistent homology. - Ev Zisselman, Itai Lavie, Daniel Soudry, Aviv Tamar:
Explore to Generalize in Zero-Shot RL. - Dadallage A. R. Silva, Spencer Whitehead, Christopher T. Lengerich, Hugh Leather:
CoLLAT: On Adding Fine-grained Audio Understanding to Language Models using Token-Level Locked-Language Tuning. - Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré:
Abide by the law and follow the flow: conservation laws for gradient flows. - Marcel Torne Villasevil, Max Balsells, Zihan Wang, Samedh Desai, Tao Chen, Pulkit Agrawal, Abhishek Gupta:
Breadcrumbs to the Goal: Supervised Goal Selection from Human-in-the-Loop Feedback. - Neel Guha, Mayee F. Chen, Kush Bhatia, Azalia Mirhoseini, Frederic Sala, Christopher Ré:
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification. - Dror Freirich, Tomer Michaeli, Ron Meir:
Perceptual Kalman Filters: Online State Estimation under a Perfect Perceptual-Quality Constraint. - Yuhang Li, Tamar Geller, Youngeun Kim, Priyadarshini Panda:
SEENN: Towards Temporal Spiking Early Exit Neural Networks. - Yeshu Li, Brian D. Ziebart:
Distributionally Robust Skeleton Learning of Discrete Bayesian Networks. - Kanishk Jain, Shyamgopal Karthik, Vineet Gandhi:
Test-Time Amendment with a Coarse Classifier for Fine-Grained Classification. - Xing Gao, Yu Cheng:
Robust Matrix Sensing in the Semi-Random Model. - Manu Srinath Halvagal, Axel Laborieux, Friedemann Zenke:
Implicit variance regularization in non-contrastive SSL. - Björn Deiseroth, Mayukh Deb, Samuel Weinbach, Manuel Brack, Patrick Schramowski, Kristian Kersting:
ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation. - Kirill Neklyudov, Jannes Nys, Luca A. Thiede, Juan Carrasquilla, Qiang Liu, Max Welling, Alireza Makhzani:
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation. - Michael Hassid, Tal Remez, Tu Anh Nguyen, Itai Gat, Alexis Conneau, Felix Kreuk, Jade Copet, Alexandre Défossez, Gabriel Synnaeve, Emmanuel Dupoux, Roy Schwartz, Yossi Adi:
Textually Pretrained Speech Language Models. - Isay Katsman, Eric Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser Nam Lim, Christopher De Sa:
Riemannian Residual Neural Networks. - Ruian Wang, Zixiong Wang, Yunxiao Zhang, Shuang-Min Chen, Shiqing Xin, Changhe Tu, Wenping Wang:
Aligning Gradient and Hessian for Neural Signed Distance Function. - Yan Xia, Hai Huang, Jieming Zhu, Zhou Zhao:
Achieving Cross Modal Generalization with Multimodal Unified Representation. - Yefan Zhou, Tianyu Pang, Keqin Liu, Charles H. Martin, Michael W. Mahoney, Yaoqing Yang:
Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training. - Zi Wang, Alexander Ku, Jason Baldridge, Tom Griffiths, Been Kim:
Gaussian Process Probes (GPP) for Uncertainty-Aware Probing. - Hong-Xing Yu, Yang Zheng, Yuan Gao, Yitong Deng, Bo Zhu, Jiajun Wu:
Inferring Hybrid Neural Fluid Fields from Videos. - Honghua Dong, Jiawei Xu, Yu Yang, Rui Zhao, Shiwen Wu, Chun Yuan, Xiu Li, Chris J. Maddison, Lei Han:
MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy. - Jann Spiess, Guido Imbens, Amar Venugopal:
Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control. - Zhenglin Huang, Xiaoan Bao, Na Zhang, Qingqi Zhang, Xiao Tu, Biao Wu, Xi Yang:
IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers. - Seungyong Moon, Junyoung Yeom, Bumsoo Park, Hyun Oh Song:
Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning. - Siobhan Mackenzie Hall, Fernanda Gonçalves Abrantes, Hanwen Zhu, Grace Sodunke, Aleksandar Shtedritski, Hannah Rose Kirk:
VisoGender: A dataset for benchmarking gender bias in image-text pronoun resolution. - Avani Gupta, Saurabh Saini, P. J. Narayanan:
Concept Distillation: Leveraging Human-Centered Explanations for Model Improvement. - Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N. Balasubramanian:
Mitigating the Effect of Incidental Correlations on Part-based Learning. - Ivana Balazevic, David Steiner, Nikhil Parthasarathy, Relja Arandjelovic, Olivier J. Hénaff:
Towards In-context Scene Understanding. - Nishanth Anand, Doina Precup:
Prediction and Control in Continual Reinforcement Learning. - Johann Brehmer, Joey Bose, Pim de Haan, Taco S. Cohen:
EDGI: Equivariant Diffusion for Planning with Embodied Agents. - Guoyuan An, Juhyeong Seon, Inkyu An, Yuchi Huo, Sung-Eui Yoon:
Topological RANSAC for instance verification and retrieval without fine-tuning. - Quan Xiao, Songtao Lu, Tianyi Chen:
An Alternating Optimization Method for Bilevel Problems under the Polyak-Łojasiewicz Condition. - Jiaze Qiu:
Sub-optimality of the Naive Mean Field approximation for proportional high-dimensional Linear Regression. - Vasilis Kontonis, Mingchen Ma, Christos Tzamos:
The Gain from Ordering in Online Learning. - Sebastian Sanokowski, Wilhelm Berghammer, Sepp Hochreiter, Sebastian Lehner:
Variational Annealing on Graphs for Combinatorial Optimization. - Zhimeng Stephen Jiang, Xiaotian Han, Hongye Jin, Guanchu Wang, Rui Chen, Na Zou, Xia Hu:
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach. - Bryan Andrews, Joseph D. Ramsey, Ruben Sanchez-Romero, Jazmin Camchong, Erich Kummerfeld:
Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow Shrink Trees. - Zeyu Zhang, Chaozhuo Li, Xu Chen, Xing Xie:
Bayesian Active Causal Discovery with Multi-Fidelity Experiments. - Yunzhe Qi, Yikun Ban, Tianxin Wei, Jiaru Zou, Huaxiu Yao, Jingrui He:
Meta-Learning with Neural Bandit Scheduler. - James Liang, Yiming Cui, Qifan Wang, Tong Geng, Wenguan Wang, Dongfang Liu:
ClusterFomer: Clustering As A Universal Visual Learner. - Man Yao, Jiakui Hu, Zhaokun Zhou, Li Yuan, Yonghong Tian, Bo Xu, Guoqi Li:
Spike-driven Transformer. - Julian Rossbroich, Friedemann Zenke:
Dis-inhibitory neuronal circuits can control the sign of synaptic plasticity. - Nikita Kornilov, Ohad Shamir, Aleksandr V. Lobanov, Darina Dvinskikh, Alexander V. Gasnikov, Innokentiy Shibaev, Eduard Gorbunov, Samuel Horváth:
Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance. - Yuanyuan Wang, Xi Geng, Wei Huang, Biwei Huang, Mingming Gong:
Generator Identification for Linear SDEs with Additive and Multiplicative Noise. - Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan H. Greenewald, Akash Srivastava:
Post-processing Private Synthetic Data for Improving Utility on Selected Measures. - Elisa Nguyen, Minjoon Seo, Seong Joon Oh:
A Bayesian Approach To Analysing Training Data Attribution In Deep Learning. - Amir Akbarnejad, Gilbert Bigras, Nilanjan Ray:
GPEX, A Framework For Interpreting Artificial Neural Networks. - Jieyu Zhang, Bohan Wang, Zhengyu Hu, Pang Wei Koh, Alexander J. Ratner:
On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training. - Marco Celotto, Jan Bím, Alejandro Tlaie, Vito De Feo, Alessandro Toso, Stefan Lemke, Daniel Chicharro, Hamed Nili, Malte Bieler, Ileana L. Hanganu-Opatz, Tobias Donner, Andrea Brovelli, Stefano Panzeri:
An information-theoretic quantification of the content of communication between brain regions. - Anant Raj, Umut Simsekli, Alessandro Rudi:
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. - Hiren Madhu, Sundeep Prabhakar Chepuri:
TopoSRL: Topology preserving self-supervised Simplicial Representation Learning. - Xiaoyu Tian, Tao Jiang, Longfei Yun, Yucheng Mao, Huitong Yang, Yue Wang, Yilun Wang, Hang Zhao:
Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving. - Pascal Notin, Aaron Kollasch, Daniel Ritter, Lood van Niekerk, Steffanie Paul, Han Spinner, Nathan J. Rollins, Ada Shaw, Rose Orenbuch, Ruben Weitzman, Jonathan Frazer, Mafalda Dias, Dinko Franceschi, Yarin Gal, Debora S. Marks:
ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design. - Aditya Vardhan Varre, Maria-Luiza Vladarean, Loucas Pillaud-Vivien, Nicolas Flammarion:
On the spectral bias of two-layer linear networks. - Yushan Zhang, Johan Edstedt, Bastian Wandt, Per-Erik Forssén, Maria Magnusson, Michael Felsberg:
GMSF: Global Matching Scene Flow. - Ziyi Huang, Henry Lam, Haofeng Zhang:
Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks. - Jiajun Tang, Haofeng Zhong, Shuchen Weng, Boxin Shi:
LuminAIRe: Illumination-Aware Conditional Image Repainting for Lighting-Realistic Generation. - Ron Levie:
A graphon-signal analysis of graph neural networks. - Simon Steshin:
Lo-Hi: Practical ML Drug Discovery Benchmark. - Tiffany Ding, Anastasios Angelopoulos, Stephen Bates, Michael I. Jordan, Ryan J. Tibshirani:
Class-Conditional Conformal Prediction with Many Classes. - Xiao Zhang, Ninglu Shao, Zihua Si, Jun Xu, Wenhan Wang, Hanjing Su, Ji-Rong Wen:
Reward Imputation with Sketching for Contextual Batched Bandits. - Nataly Brukhim, Miro Dudík, Aldo Pacchiano, Robert E. Schapire:
A Unified Model and Dimension for Interactive Estimation. - Moses Charikar, Monika Henzinger, Lunjia Hu, Maximilian Vötsch, Erik Waingarten:
Simple, Scalable and Effective Clustering via One-Dimensional Projections. - Syamantak Kumar, Purnamrita Sarkar:
Streaming PCA for Markovian Data. - Beier Zhu, Kaihua Tang, Qianru Sun, Hanwang Zhang:
Generalized Logit Adjustment: Calibrating Fine-tuned Models by Removing Label Bias in Foundation Models. - Shijie Wang, Jianlong Chang, Haojie Li, Zhihui Wang, Wanli Ouyang, Qi Tian:
Learning to Parameterize Visual Attributes for Open-set Fine-grained Retrieval. - Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky:
Learning List-Level Domain-Invariant Representations for Ranking. - Joon-Hyuk Ko, Hankyul Koh, Nojun Park, Wonho Jhe:
Homotopy-based training of NeuralODEs for accurate dynamics discovery. - Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan:
Simplifying and Empowering Transformers for Large-Graph Representations. - Jun Xia, Lecheng Zhang, Xiao Zhu, Yue Liu, Zhangyang Gao, Bozhen Hu, Cheng Tan, Jiangbin Zheng, Siyuan Li, Stan Z. Li:
Understanding the Limitations of Deep Models for Molecular property prediction: Insights and Solutions. - Jacob A. Zavatone-Veth, Paul Masset, William L. Tong, Joseph D. Zak, Venkatesh Murthy, Cengiz Pehlevan:
Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb. - Atul Kumar Sinha, Daniele Paliotta, Bálint Máté, John A. Raine, Tobias Golling, François Fleuret:
SUPA: A Lightweight Diagnostic Simulator for Machine Learning in Particle Physics. - Artur P. Toshev, Gianluca Galletti, Fabian Fritz, Stefan Adami, Nikolaus A. Adams:
LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite. - Haris Aziz, Evi Micha, Nisarg Shah:
Group Fairness in Peer Review. - Haoran He, Chenjia Bai, Kang Xu, Zhuoran Yang, Weinan Zhang, Dong Wang, Bin Zhao, Xuelong Li:
Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning. - Sayantan Choudhury, Eduard Gorbunov, Nicolas Loizou:
Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions. - Tianhe Wu, Shuwei Shi, Haoming Cai, Mingdeng Cao, Jing Xiao, Yinqiang Zheng, Yujiu Yang:
Assessor360: Multi-sequence Network for Blind Omnidirectional Image Quality Assessment. - Ruihan Yang, Stephan Mandt:
Lossy Image Compression with Conditional Diffusion Models. - Pierre Marion, Raphaël Berthier:
Leveraging the two-timescale regime to demonstrate convergence of neural networks. - Bailin Wang, Zi Wang, Xuezhi Wang, Yuan Cao, Rif A. Saurous, Yoon Kim:
Grammar Prompting for Domain-Specific Language Generation with Large Language Models. - Duc Hoang, Souvik Kundu, Shiwei Liu, Zhangyang Wang:
Don't just prune by magnitude! Your mask topology is a secret weapon. - Howard Zhong, Samarth Mishra, Donghyun Kim, SouYoung Jin, Rameswar Panda, Hilde Kuehne, Leonid Karlinsky, Venkatesh Saligrama, Aude Oliva, Rogério Feris:
Learning Human Action Recognition Representations Without Real Humans. - Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan A. K. Suykens:
Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation. - Alexander Shmakov, Kevin Greif, Michael James Fenton, Aishik Ghosh, Pierre Baldi, Daniel Whiteson:
End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics. - Michael Schlichtkrull, Zhijiang Guo, Andreas Vlachos:
AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web. - Yuanshao Zhu, Yongchao Ye, Shiyao Zhang, Xiangyu Zhao, James Yu:
DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model. - Julian Coda-Forno, Marcel Binz, Zeynep Akata, Matt M. Botvinick, Jane X. Wang, Eric Schulz:
Meta-in-context learning in large language models. - Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurélien Lucchi, Thomas Hofmann:
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers. - Dohyeok Lee, Seungyub Han, Taehyun Cho, Jungwoo Lee:
SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning. - Xiaosong Ma, Jie Zhang, Song Guo, Wenchao Xu:
SwapPrompt: Test-Time Prompt Adaptation for Vision-Language Models. - Quoc-Tung Le, Rémi Gribonval, Elisa Riccietti:
Does a sparse ReLU network training problem always admit an optimum ? - Tao Huang, Yuan Zhang, Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Chang Xu:
Knowledge Diffusion for Distillation. - Minyoung Kim, Timothy M. Hospedales:
BayesTune: Bayesian Sparse Deep Model Fine-tuning. - Yaoyu Zhu, Wei Fang, Xiaodong Xie, Tiejun Huang, Zhaofei Yu:
Exploring Loss Functions for Time-based Training Strategy in Spiking Neural Networks. - Louis Sharrock, Lester Mackey, Christopher Nemeth:
Learning Rate Free Bayesian Inference in Constrained Domains. - Kang Han, Wei Xiang, Lu Yu:
Volume Feature Rendering for Fast Neural Radiance Field Reconstruction. - Pengjie Gu, Xinyu Cai, Dong Xing, Xinrun Wang, Mengchen Zhao, Bo An:
Offline RL with Discrete Proxy Representations for Generalizability in POMDPs. - Siyuan Sun, Hongyang Gao:
Meta-AdaM: An Meta-Learned Adaptive Optimizer with Momentum for Few-Shot Learning. - Thanh-Dat Truong, Hoang-Quan Nguyen, Bhiksha Raj, Khoa Luu:
Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments. - Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, Himabindu Lakkaraju:
Post Hoc Explanations of Language Models Can Improve Language Models. - Diederik P. Kingma, Ruiqi Gao:
Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation. - Zangwei Zheng, Xiaozhe Ren, Fuzhao Xue, Yang Luo, Xin Jiang, Yang You:
Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline. - Siliang Zeng, Chenliang Li, Alfredo García, Mingyi Hong:
When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning. - Matthew Wallingford, Vivek Ramanujan, Alex Fang, Aditya Kusupati, Roozbeh Mottaghi, Aniruddha Kembhavi, Ludwig Schmidt, Ali Farhadi:
Neural Priming for Sample-Efficient Adaptation. - Meshi Bashari, Amir Epstein, Yaniv Romano, Matteo Sesia:
Derandomized novelty detection with FDR control via conformal e-values. - Eldar Kurtic, Elias Frantar, Dan Alistarh:
ZipLM: Inference-Aware Structured Pruning of Language Models. - Daogao Liu, Arun Ganesh, Sewoong Oh, Abhradeep Guha Thakurta:
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks. - Shresth Grover, Vibhav Vineet, Yogesh S. Rawat:
Revealing the unseen: Benchmarking video action recognition under occlusion. - Jiaqi Xue, Mengxin Zheng, Ting Hua, Yilin Shen, Yepeng Liu, Ladislau Bölöni, Qian Lou:
TrojLLM: A Black-box Trojan Prompt Attack on Large Language Models. - Verónica Álvarez, Santiago Mazuelas, José Antonio Lozano:
Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees. - Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen, Sivaraman Balakrishnan, Zachary C. Lipton, Yu-Xiang Wang:
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms. - Nikhil Parthasarathy, S. M. Ali Eslami, João Carreira, Olivier J. Hénaff:
Self-supervised video pretraining yields robust and more human-aligned visual representations. - Di Qi, Tong Yang, Xiangyu Zhang:
Slot-guided Volumetric Object Radiance Fields. - Jihun Yun, Eunho Yang:
Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds. - Xuanle Zhao, Duzhen Zhang, Liyuan Han, Tielin Zhang, Bo Xu:
ODE-based Recurrent Model-free Reinforcement Learning for POMDPs. - Tonghan Wang, Paul Duetting, Dmitry Ivanov, Inbal Talgam-Cohen, David C. Parkes:
Deep Contract Design via Discontinuous Networks. - Jianwei Tang, Jiangxin Sun, Xiaotong Lin, Lifang Zhang, Wei-Shi Zheng, Jian-Fang Hu:
Temporal Continual Learning with Prior Compensation for Human Motion Prediction. - Ethan Epperly, Elvira Moreno:
Kernel Quadrature with Randomly Pivoted Cholesky. - Tobit Klug, Dogukan Atik, Reinhard Heckel:
Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods. - Youguang Chen, George Biros:
FIRAL: An Active Learning Algorithm for Multinomial Logistic Regression. - Jiarong Ding, Xuehu Zhu:
AMDP: An Adaptive Detection Procedure for False Discovery Rate Control in High-Dimensional Mediation Analysis. - Guy Gaziv, Michael J. Lee, James J. DiCarlo:
Strong and Precise Modulation of Human Percepts via Robustified ANNs. - Pandeng Li, Chen-Wei Xie, Hongtao Xie, Liming Zhao, Lei Zhang, Yun Zheng, Deli Zhao, Yongdong Zhang:
MomentDiff: Generative Video Moment Retrieval from Random to Real. - Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain:
Experimental Designs for Heteroskedastic Variance. - Qing Li, Huifang Feng, Kanle Shi, Yue Gao, Yi Fang, Yu-Shen Liu, Zhizhong Han:
NeuralGF: Unsupervised Point Normal Estimation by Learning Neural Gradient Function. - Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan C. Kao:
Gacs-Korner Common Information Variational Autoencoder. - Nora Belrose, David Schneider-Joseph, Shauli Ravfogel, Ryan Cotterell, Edward Raff, Stella Biderman:
LEACE: Perfect linear concept erasure in closed form. - Dayana Savostianova, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco:
Robust low-rank training via approximate orthonormal constraints. - Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, Zhi-Ming Ma, Omar Yaghi, Animashree Anandkumar, Christian Borgs, Jennifer T. Chayes, Hongyu Guo, Jian Tang:
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials. - Ethan Weinberger, Ian Covert, Su-In Lee:
Feature Selection in the Contrastive Analysis Setting. - Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao, Aaron Adcock, Laurens van der Maaten, Deepti Ghadiyaram, Olga Russakovsky:
GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition. - Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro:
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. - Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh:
Unleashing the Power of Randomization in Auditing Differentially Private ML. - Piotr Indyk, Haike Xu:
Worst-case Performance of Popular Approximate Nearest Neighbor Search Implementations: Guarantees and Limitations. - Zeke Xie, Qian-Yuan Tang, Mingming Sun, Ping Li:
On the Overlooked Structure of Stochastic Gradients. - Jungwoo Oh, Gyubok Lee, Seongsu Bae, Joon-Myoung Kwon, Edward Choi:
ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogram. - Justin Domke, Robert M. Gower, Guillaume Garrigos:
Provable convergence guarantees for black-box variational inference. - Wenhao Ding, Laixi Shi, Yuejie Chi, Ding Zhao:
Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation. - Thuy Dung Nguyen, Tuan Nguyen, Anh Tran, Khoa D. Doan, Kok-Seng Wong:
IBA: Towards Irreversible Backdoor Attacks in Federated Learning. - Gabriel Raya, Luca Ambrogioni:
Spontaneous symmetry breaking in generative diffusion models. - Antoine Scardigli, Lukas Cavigelli, Lorenz K. Müller:
RL-based Stateful Neural Adaptive Sampling and Denoising for Real-Time Path Tracing. - Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr:
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks. - Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ali Farhadi, Ludwig Schmidt:
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness. - Asic Q. Chen, Ruian Shi, Xiang Gao, Ricardo Baptista, Rahul G. Krishnan:
Structured Neural Networks for Density Estimation and Causal Inference. - Sharan Vaswani, Amirreza Kazemi, Reza Babanezhad Harikandeh, Nicolas Le Roux:
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees. - Jian Chen, Ruiyi Zhang, Tong Yu, Rohan Sharma, Zhiqiang Xu, Tong Sun, Changyou Chen:
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels. - Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang:
Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models. - Andre Vauvelle, Benjamin Wild, Roland Eils, Spiros C. Denaxas:
Differentiable sorting for censored time-to-event data. - Weichao Mao, Haoran Qiu, Chen Wang, Hubertus Franke, Zbigniew Kalbarczyk, Ravishankar K. Iyer, Tamer Basar:
Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates with Task Similarity. - Jack H. Good, Torin Kovach, Kyle Miller, Artur Dubrawski:
Feature Learning for Interpretable, Performant Decision Trees. - Ziheng Cheng, Shiyue Zhang, Longlin Yu, Cheng Zhang:
Particle-based Variational Inference with Generalized Wasserstein Gradient Flow. - Anand Brahmbhatt, Rishi Saket, Aravindan Raghuveer:
PAC Learning Linear Thresholds from Label Proportions. - Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P. Gomes, Zhi-Ming Ma:
A new perspective on building efficient and expressive 3D equivariant graph neural networks. - Xiaobin Rui, Zhixiao Wang, Jiayu Zhao, Lichao Sun, Wei Chen:
Scalable Fair Influence Maximization. - Yeyuan Chen, Dingmin Wang:
Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs. - Guillermo Ortiz-Jiménez, Alessandro Favero, Pascal Frossard:
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models. - Lu Yan, Zhuo Zhang, Guanhong Tao, Kaiyuan Zhang, Xuan Chen, Guangyu Shen, Xiangyu Zhang:
ParaFuzz: An Interpretability-Driven Technique for Detecting Poisoned Samples in NLP. - Aditya Vora, Akshay Gadi Patil, Hao Zhang:
DiViNeT: 3D Reconstruction from Disparate Views using Neural Template Regularization. - Zakaria Mhammedi, Adam Block, Dylan J. Foster, Alexander Rakhlin:
Efficient Model-Free Exploration in Low-Rank MDPs. - Denizalp Goktas, Arjun Prakash, Amy Greenwald:
Convex-Concave Zero-Sum Stochastic Stackelberg Games. - Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten:
Near-Linear Time Algorithm for the Chamfer Distance. - Jose H. Blanchet, Miao Lu, Tong Zhang, Han Zhong:
Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage. - Kihyuk Sohn, Lu Jiang, Jarred Barber, Kimin Lee, Nataniel Ruiz, Dilip Krishnan, Huiwen Chang, Yuanzhen Li, Irfan Essa, Michael Rubinstein, Yuan Hao, Glenn Entis, Irina Blok, Daniel Castro Chin:
StyleDrop: Text-to-Image Synthesis of Any Style. - Konstantin Makarychev, Liren Shan:
Random Cuts are Optimal for Explainable k-Medians. - Dami Choi, Derrick Xin, Hamid Dadkhahi, Justin Gilmer, Ankush Garg, Orhan Firat, Chih-Kuan Yeh, Andrew M. Dai, Behrooz Ghorbani:
Order Matters in the Presence of Dataset Imbalance for Multilingual Learning. - Yaru Hao, Zewen Chi, Li Dong, Furu Wei:
Optimizing Prompts for Text-to-Image Generation. - Meena Jagadeesan, Michael I. Jordan, Jacob Steinhardt, Nika Haghtalab:
Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition. - David Brandfonbrener, Ofir Nachum, Joan Bruna:
Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation. - Iosif Sakos, Emmanouil V. Vlatakis-Gkaragkounis, Panayotis Mertikopoulos, Georgios Piliouras:
Exploiting hidden structures in non-convex games for convergence to Nash equilibrium. - Shengzhuang Chen, Long-Kai Huang, Jonathan Richard Schwarz, Yilun Du, Ying Wei:
Secure Out-of-Distribution Task Generalization with Energy-Based Models. - Evangelos Ntavelis, Aliaksandr Siarohin, Kyle Olszewski, Chaoyang Wang, Luc Van Gool, Sergey Tulyakov:
Autodecoding Latent 3D Diffusion Models. - Hsiao-Yu Tung, Mingyu Ding, Zhenfang Chen, Daniel Bear, Chuang Gan, Josh Tenenbaum, Dan Yamins, Judith E. Fan, Kevin A. Smith:
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties. - Hao Zheng, Regina Lee, Yuqian Lu:
HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge Understanding. - Xiao-Yang Liu, Zeliang Zhang:
Classical Simulation of Quantum Circuits: Parallel Environments and Benchmark. - Sophia Sanborn, Nina Miolane:
A General Framework for Robust G-Invariance in G-Equivariant Networks. - Michael Wornow, Rahul Thapa, Ethan Steinberg, Jason A. Fries, Nigam Shah:
EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models. - Kushin Mukherjee, Holly Huey, Xuanchen Lu, Yael Vinker, Rio Aguina-Kang, Ariel Shamir, Judith E. Fan:
SEVA: Leveraging sketches to evaluate alignment between human and machine visual abstraction. - Devleena Das, Sonia Chernova, Been Kim:
State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding. - Tom Coates, Alexander M. Kasprzyk, Sara Veneziale:
Machine learning detects terminal singularities. - Bingyi Kang, Xiao Ma, Chao Du, Tianyu Pang, Shuicheng Yan:
Efficient Diffusion Policies For Offline Reinforcement Learning. - Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu:
Selective Sampling and Imitation Learning via Online Regression. - Phoenix Williams, Ke Li:
CamoPatch: An Evolutionary Strategy for Generating Camoflauged Adversarial Patches. - Sneha Kudugunta, Isaac Caswell, Biao Zhang, Xavier Garcia, Derrick Xin, Aditya Kusupati, Romi Stella, Ankur Bapna, Orhan Firat:
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset. - Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang, Zhuoran Yang:
Learning Regularized Monotone Graphon Mean-Field Games. - Weiwen Xu, Xin Li, Wenxuan Zhang, Meng Zhou, Wai Lam, Luo Si, Lidong Bing:
From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Models to Pre-trained Machine Reader. - Xiuye Gu, Yin Cui, Jonathan Huang, Abdullah Rashwan, Xuan Yang, Xingyi Zhou, Golnaz Ghiasi, Weicheng Kuo, Huizhong Chen, Liang-Chieh Chen, David A. Ross:
DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model. - Yunxiang Zhang, Xiaojun Wan:
SituatedGen: Incorporating Geographical and Temporal Contexts into Generative Commonsense Reasoning. - Jongheon Jeong, Jinwoo Shin:
Multi-scale Diffusion Denoised Smoothing. - Phillip Lippe, Bas Veeling, Paris Perdikaris, Richard E. Turner, Johannes Brandstetter:
PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers. - Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine:
Accelerating Exploration with Unlabeled Prior Data. - Stefan Matthes, Zhiwei Han, Hao Shen:
Towards a Unified Framework of Contrastive Learning for Disentangled Representations. - Kiarash Banihashem, MohammadTaghi Hajiaghayi, Suho Shin, Max Springer:
An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits. - Jiawei Du, Qin Shi, Joey Tianyi Zhou:
Sequential Subset Matching for Dataset Distillation. - Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani, Erik Vee:
SLaM: Student-Label Mixing for Distillation with Unlabeled Examples. - Yifei Zhang, Hao Zhu, Yankai Chen, Zixing Song, Piotr Koniusz, Irwin King:
Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective. - Linhao Qu, Xiaoyuan Luo, Kexue Fu, Manning Wang, Zhijian Song:
The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification. - Mingxuan Ye, Yufei Kuang, Jie Wang, Yang Rui, Wengang Zhou, Houqiang Li, Feng Wu:
State Sequences Prediction via Fourier Transform for Representation Learning. - Xinrui Wang, Wenhai Wan, Chuanxing Geng, Shaoyuan Li, Songcan Chen:
Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends. - Peter Macgregor, He Sun:
Fast Approximation of Similarity Graphs with Kernel Density Estimation. - Enneng Yang, Li Shen, Zhenyi Wang, Tongliang Liu, Guibing Guo:
An Efficient Dataset Condensation Plugin and Its Application to Continual Learning. - Minsu Kim, Federico Berto, Sungsoo Ahn, Jinkyoo Park:
Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences. - Ahmad Chamma, Denis A. Engemann, Bertrand Thirion:
Statistically Valid Variable Importance Assessment through Conditional Permutations. - Le Yu, Leilei Sun, Bowen Du, Weifeng Lv:
Towards Better Dynamic Graph Learning: New Architecture and Unified Library. - Bernardo Fichera, Slava Borovitskiy, Andreas Krause, Aude Gemma Billard:
Implicit Manifold Gaussian Process Regression. - Kyusu Ahn, Byeonghyun Ko, HyunGyu Lee, Chanwoo Park, Jaejin Lee:
UDC-SIT: A Real-World Dataset for Under-Display Cameras. - Yan Dai, Kwangjun Ahn, Suvrit Sra:
The Crucial Role of Normalization in Sharpness-Aware Minimization. - Jian Yao, Weiming Liu, Haobo Fu, Yaodong Yang, Stephen McAleer, Qiang Fu, Wei Yang:
Policy Space Diversity for Non-Transitive Games. - Tristan Tomilin, Meng Fang, Yudi Zhang, Mykola Pechenizkiy:
COOM: A Game Benchmark for Continual Reinforcement Learning. - Kumar Ashutosh, Santhosh Kumar Ramakrishnan, Triantafyllos Afouras, Kristen Grauman:
Video-Mined Task Graphs for Keystep Recognition in Instructional Videos. - Ameya Velingker, Ali Kemal Sinop, Ira Ktena, Petar Velickovic, Sreenivas Gollapudi:
Affinity-Aware Graph Networks. - Runqi Lin, Chaojian Yu, Tongliang Liu:
Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization. - Syed Talal Wasim, Kabila Haile Soboka, Abdulrahman Mahmoud, Salman H. Khan, David Brooks, Gu-Yeon Wei:
Hardware Resilience Properties of Text-Guided Image Classifiers. - Jonas Schweisthal, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel:
Reliable Off-Policy Learning for Dosage Combinations. - Jiayu Chen, Vaneet Aggarwal, Tian Lan:
A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process. - Chengzhi Cao, Chao Yang, Ruimao Zhang, Shuang Li:
Discovering Intrinsic Spatial-Temporal Logic Rules to Explain Human Actions. - Shentong Mo, Enze Xie, Ruihang Chu, Lanqing Hong, Matthias Nießner, Zhenguo Li:
DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation. - Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava:
DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. - Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu:
Dynamic Sparsity Is Channel-Level Sparsity Learner. - David Liu, Máté Lengyel:
Bayesian nonparametric (non-)renewal processes for analyzing neural spike train variability. - Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu:
Evaluating Self-Supervised Learning for Molecular Graph Embeddings. - Martin Gonzalez, Nelson Fernandez Pinto, Thuy Tran, Elies Gherbi, Hatem Hajri, Nader Masmoudi:
SEEDS: Exponential SDE Solvers for Fast High-Quality Sampling from Diffusion Models. - Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao:
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. - Hongjie Chen, Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Jacob Imola, David Steurer, Stefan Tiegel:
Private estimation algorithms for stochastic block models and mixture models. - Injae Kim, Minhyuk Choi, Hyunwoo J. Kim:
UP-NeRF: Unconstrained Pose Prior-Free Neural Radiance Field. - William Swartworth, Deanna Needell, Rachel A. Ward, Mark Kong, Halyun Jeong:
Nearly Optimal Bounds for Cyclic Forgetting. - Zhangyang Gao, Cheng Tan, Yijie Zhang, Xingran Chen, Lirong Wu, Stan Z. Li:
ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics. - Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng:
Understanding and Improving Feature Learning for Out-of-Distribution Generalization. - Ido Greenberg, Shie Mannor, Gal Chechik, Eli A. Meirom:
Train Hard, Fight Easy: Robust Meta Reinforcement Learning. - Chang Lu, Chandan K. Reddy, Ping Wang, Yue Ning:
Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning. - David Loiseaux, Luis Scoccola, Mathieu Carrière, Magnus Bakke Botnan, Steve Oudot:
Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures. - Yingbin Bai, Zhongyi Han, Erkun Yang, Jun Yu, Bo Han, Dadong Wang, Tongliang Liu:
Subclass-Dominant Label Noise: A Counterexample for the Success of Early Stopping. - Ayça Takmaz, Elisabetta Fedele, Robert W. Sumner, Marc Pollefeys, Federico Tombari, Francis Engelmann:
OpenMask3D: Open-Vocabulary 3D Instance Segmentation. - Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao:
Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. - Tianyi Liu, Kejun Wu, Yi Wang, Wenyang Liu, Kim-Hui Yap, Lap-Pui Chau:
Bitstream-Corrupted Video Recovery: A Novel Benchmark Dataset and Method. - Wenqi Cui, Yan Jiang, Baosen Zhang, Yuanyuan Shi:
Structured Neural-PI Control with End-to-End Stability and Output Tracking Guarantees. - Jiuhn Song, Seonghoon Park, Honggyu An, Seokju Cho, Minseop Kwak, Sungjin Cho, Seungryong Kim:
DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation. - Qiang Gao, Xiaojun Shan, Yuchen Zhang, Fan Zhou:
Enhancing Knowledge Transfer for Task Incremental Learning with Data-free Subnetwork. - Xin Liu, Girish Narayanswamy, Akshay Paruchuri, Xiaoyu Zhang, Jiankai Tang, Yuzhe Zhang, Roni Sengupta, Shwetak N. Patel, Yuntao Wang, Daniel McDuff:
rPPG-Toolbox: Deep Remote PPG Toolbox. - Miao Xiong, Ailin Deng, Pang Wei W. Koh, Jiaying Wu, Shen Li, Jianqing Xu, Bryan Hooi:
Proximity-Informed Calibration for Deep Neural Networks. - Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom:
Toolformer: Language Models Can Teach Themselves to Use Tools. - Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu, Adil Salim:
The probability flow ODE is provably fast. - Taihei Oki, Shinsaku Sakaue:
Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case. - Naoki Egami, Musashi Hinck, Brandon M. Stewart, Hanying Wei:
Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models. - Carol Xuan Long, Hsiang Hsu, Wael Alghamdi, Flávio P. Calmon:
Individual Arbitrariness and Group Fairness. - Jongseok Park, Kyungmin Bin, Gibum Park, Sangtae Ha, Kyunghan Lee:
ASPEN: Breaking Operator Barriers for Efficient Parallelization of Deep Neural Networks. - Deeparnab Chakrabarty, Andrei Graur, Haotian Jiang, Aaron Sidford:
Parallel Submodular Function Minimization. - Yuxuan Guo, Yifan Hao, Rui Zhang, Enshuai Zhou, Zidong Du, Xishan Zhang, Xinkai Song, Yuanbo Wen, Yongwei Zhao, Xuehai Zhou, Jiaming Guo, Qi Yi, Shaohui Peng, Di Huang, Ruizhi Chen, Qi Guo, Yunji Chen:
Emergent Communication for Rules Reasoning. - Matthew Bendel, Rizwan Ahmad, Philip Schniter:
A Regularized Conditional GAN for Posterior Sampling in Image Recovery Problems. - Alexander Meulemans, Simon Schug, Seijin Kobayashi, Nathaniel Daw, Gregory Wayne:
Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis. - Noah Wiederhold, Ava Megyeri, DiMaggio Paris, Sean Banerjee, Natasha Banerjee:
HOH: Markerless Multimodal Human-Object-Human Handover Dataset with Large Object Count. - Matan Schliserman, Tomer Koren:
Tight Risk Bounds for Gradient Descent on Separable Data. - Alejandro Escontrela, Ademi Adeniji, Wilson Yan, Ajay Jain, Xue Bin Peng, Ken Goldberg, Youngwoon Lee, Danijar Hafner, Pieter Abbeel:
Video Prediction Models as Rewards for Reinforcement Learning. - Xiaoyan Hu, Ho-fung Leung:
Provably (More) Sample-Efficient Offline RL with Options. - Yun Xing, Jian Kang, Aoran Xiao, Jiahao Nie, Ling Shao, Shijian Lu:
Rewrite Caption Semantics: Bridging Semantic Gaps for Language-Supervised Semantic Segmentation. - Lai Wei, Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu:
Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders. - Andi Peng, Mycal Tucker, Eoin M. Kenny, Noga Zaslavsky, Pulkit Agrawal, Julie A. Shah:
Human-Guided Complexity-Controlled Abstractions. - Ethan Pronovost, Meghana Reddy Ganesina, Noureldin Hendy, Zeyu Wang, Andres Morales, Kai Wang, Nick Roy:
Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion. - Ngoc-Bao Nguyen, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Ngai-Man Cheung:
Label-Only Model Inversion Attacks via Knowledge Transfer. - Xin Zou, Weiwei Liu:
On the Adversarial Robustness of Out-of-distribution Generalization Models. - Devon R. Graham, Kevin Leyton-Brown, Tim Roughgarden:
Utilitarian Algorithm Configuration. - Yuanshi Liu, Cong Fang, Tong Zhang:
Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee. - Marc Jourdan, Rémy Degenne:
Non-Asymptotic Analysis of a UCB-based Top Two Algorithm. - Filippo Vannella, Alexandre Proutière, Jaeseong Jeong:
Statistical and Computational Trade-off in Multi-Agent Multi-Armed Bandits. - Simone Rossi, Ankit Singh, Thomas Hannagan:
On permutation symmetries in Bayesian neural network posteriors: a variational perspective. - Liyuan Wang, Jingyi Xie, Xingxing Zhang, Mingyi Huang, Hang Su, Jun Zhu:
Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality. - Pedro O. Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, Omar Mahmood, Andrew M. Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi:
3D molecule generation by denoising voxel grids. - Sida Wang:
Accessing Higher Dimensions for Unsupervised Word Translation. - Feiyang Wu, Jingyang Ke, Anqi Wu:
Inverse Reinforcement Learning with the Average Reward Criterion. - Tao Yang, Yuwang Wang, Yan Lu, Nanning Zheng:
DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models. - Matheus Aparecido do Carmo Alves, Amokh Varma, Yehia Elkhatib, Leandro Soriano Marcolino:
Information-guided Planning: An Online Approach for Partially Observable Problems. - Frederik Warburg, Marco Miani, Silas Brack, Søren Hauberg:
Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval. - Jonathan Zedaka, Elisha Halperin, Evgeny Blaichman, Amit Berman:
Neural Modulation for Flash Memory: An Unsupervised Learning Framework for Improved Reliability. - Wei-Ning Chen, Dan Song, Ayfer Özgür, Peter Kairouz:
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation. - Maximilian Müller, Tiffany Vlaar, David Rolnick, Matthias Hein:
Normalization Layers Are All That Sharpness-Aware Minimization Needs. - Artun Saday, Yasar Cahit Yildirim, Cem Tekin:
Robust Bayesian Satisficing. - Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Núñez, James Lottes, Qing Wang, Yi-Fan Chen, John Anderson, Fei Sha:
Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations. - Ta Duy Nguyen, Alina Ene, Huy Nguyen:
On the Generalization Error of Stochastic Mirror Descent for Quadratically-Bounded Losses: an Improved Analysis. - Jungwuk Park, Dong-Jun Han, Jinho Kim, Shiqiang Wang, Christopher G. Brinton, Jaekyun Moon:
StableFDG: Style and Attention Based Learning for Federated Domain Generalization. - Yu Zhang, Yepeng Liu, Duoqian Miao, Qi Zhang, Yiwei Shi, Liang Hu:
MG-ViT: A Multi-Granularity Method for Compact and Efficient Vision Transformers. - Yizhou Chen, Anxiang Zeng, Qingtao Yu, Kerui Zhang, Yuanpeng Cao, Kangle Wu, Guangda Huzhang, Han Yu, Zhiming Zhou:
Recurrent Temporal Revision Graph Networks. - Jishnu Ray Chowdhury, Cornelia Caragea:
Recursion in Recursion: Two-Level Nested Recursion for Length Generalization with Scalability. - Jing Gong, Minsheng Hao, Xingyi Cheng, Xin Zeng, Chiming Liu, Jianzhu Ma, Xuegong Zhang, Taifeng Wang, Le Song:
xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data. - Di Huang, Ziyuan Nan, Xing Hu, Pengwei Jin, Shaohui Peng, Yuanbo Wen, Rui Zhang, Zidong Du, Qi Guo, Yewen Pu, Yunji Chen:
ANPL: Towards Natural Programming with Interactive Decomposition. - Markus Utke, Ulrike Schmidt-Kraepelin:
Anonymous and Copy-Robust Delegations for Liquid Democracy. - Kamil Dreczkowski, Antoine Grosnit, Haitham Bou-Ammar:
Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization. - Lujun Li, Peijie Dong, Anggeng Li, Zimian Wei, Ya Yang:
KD-Zero: Evolving Knowledge Distiller for Any Teacher-Student Pairs. - Zeyu Sun, Dogyoon Song, Alfred O. Hero III:
Minimum-Risk Recalibration of Classifiers. - Kaichen Zhou, Jia-Xing Zhong, Sangyun Shin, Kai Lu, Yiyuan Yang, Andrew Markham, Niki Trigoni:
DynPoint: Dynamic Neural Point For View Synthesis. - Shahriar Talebi, Amirhossein Taghvaei, Mehran Mesbahi:
Data-driven Optimal Filtering for Linear Systems with Unknown Noise Covariances. - Zhizhang Yuan, Daoze Zhang, Yang Yang, Junru Chen, Yafeng Li:
PPi: Pretraining Brain Signal Model for Patient-independent Seizure Detection. - Qing Wu, Lixuan Chen, Ce Wang, Hongjiang Wei, S. Kevin Zhou, Jingyi Yu, Yuyao Zhang:
Unsupervised Polychromatic Neural Representation for CT Metal Artifact Reduction. - Yash Jain, Harkirat S. Behl, Zsolt Kira, Vibhav Vineet:
DAMEX: Dataset-aware Mixture-of-Experts for visual understanding of mixture-of-datasets. - Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu:
FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective. - Francesca Bartolucci, Emmanuel de Bézenac, Bogdan Raonic, Roberto Molinaro, Siddhartha Mishra, Rima Alaifari:
Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning. - Lorenzo Perini, Jesse Davis:
Unsupervised Anomaly Detection with Rejection. - Jingkang Yang, Jun Cen, Wenxuan Peng, Shuai Liu, Fangzhou Hong, Xiangtai Li, Kaiyang Zhou, Qifeng Chen, Ziwei Liu:
4D Panoptic Scene Graph Generation. - Zhiyuan Ren, Yiyang Su, Xiaoming Liu:
ChatGPT-Powered Hierarchical Comparisons for Image Classification. - Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou:
Module-wise Adaptive Distillation for Multimodality Foundation Models. - Ida Momennejad, Hosein Hasanbeig, Felipe Vieira Frujeri, Hiteshi Sharma, Nebojsa Jojic, Hamid Palangi, Robert Osazuwa Ness, Jonathan Larson:
Evaluating Cognitive Maps and Planning in Large Language Models with CogEval. - Yutong Xie, Mingze Yuan, Bin Dong, Quanzheng Li:
Unsupervised Image Denoising with Score Function. - Milan Ganai, Zheng Gong, Chenning Yu, Sylvia L. Herbert, Sicun Gao:
Iterative Reachability Estimation for Safe Reinforcement Learning. - Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu:
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. - Cheng Tan, Siyuan Li, Zhangyang Gao, Wenfei Guan, Zedong Wang, Zicheng Liu, Lirong Wu, Stan Z. Li:
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning. - Gwen Legate, Nicolas Bernier, Lucas Page-Caccia, Edouard Oyallon, Eugene Belilovsky:
Guiding The Last Layer in Federated Learning with Pre-Trained Models. - Henry C. Bendekgey, Gabe Hope, Erik B. Sudderth:
Unbiased learning of deep generative models with structured discrete representations. - Namyong Park, Ryan A. Rossi, Xing Wang, Antoine Simoulin, Nesreen K. Ahmed, Christos Faloutsos:
GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection. - Shalev Lifshitz, Keiran Paster, Harris Chan, Jimmy Ba, Sheila A. McIlraith:
STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. - Xinran Zhao, Hongming Zhang, Xiaoman Pan, Wenlin Yao, Dong Yu, Jianshu Chen:
Thrust: Adaptively Propels Large Language Models with External Knowledge. - Yifan Zhang, Qingsong Wen, Xue Wang, Weiqi Chen, Liang Sun, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan:
OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling. - Tony Lee, Michihiro Yasunaga, Chenlin Meng, Yifan Mai, Joon Sung Park, Agrim Gupta, Yunzhi Zhang, Deepak Narayanan, Hannah Teufel, Marco Bellagente, Minguk Kang, Taesung Park, Jure Leskovec, Jun-Yan Zhu, Fei-Fei Li, Jiajun Wu, Stefano Ermon, Percy Liang:
Holistic Evaluation of Text-to-Image Models. - Souhaib Attaiki, Maks Ovsjanikov:
Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction. - DongHyeok Shin, Seungjae Shin, Il-Chul Moon:
Frequency Domain-Based Dataset Distillation. - Lisha Chen, Heshan Devaka Fernando, Yiming Ying, Tianyi Chen:
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance. - Meng Wei, Xiaoyu Yue, Wenwei Zhang, Shu Kong, Xihui Liu, Jiangmiao Pang:
OV-PARTS: Towards Open-Vocabulary Part Segmentation. - Liangyu Chen, Bo Li, Sheng Shen, Jingkang Yang, Chunyuan Li, Kurt Keutzer, Trevor Darrell, Ziwei Liu:
Large Language Models are Visual Reasoning Coordinators. - Zhijin Ge, Xiaosen Wang, Hongying Liu, Fanhua Shang, Yuanyuan Liu:
Boosting Adversarial Transferability by Achieving Flat Local Maxima. - Yuchen Yan, Yuzhong Chen, Huiyuan Chen, Minghua Xu, Mahashweta Das, Hao Yang, Hanghang Tong:
From Trainable Negative Depth to Edge Heterophily in Graphs. - Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao:
ADGym: Design Choices for Deep Anomaly Detection. - Anh Thai, Ahmad Humayun, Stefan Stojanov, Zixuan Huang, Bikram Boote, James M. Rehg:
Low-shot Object Learning with Mutual Exclusivity Bias. - Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang:
GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks. - Gaon An, Junhyeok Lee, Xingdong Zuo, Norio Kosaka, Kyung-Min Kim, Hyun Oh Song:
Direct Preference-based Policy Optimization without Reward Modeling. - Jiawen Chen, Wancen Mu, Yun Li, Didong Li:
On the Identifiability and Interpretability of Gaussian Process Models. - Shiyan Chen, Jiyuan Zhang, Yajing Zheng, Tiejun Huang, Zhaofei Yu:
Enhancing Motion Deblurring in High-Speed Scenes with Spike Streams. - Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Sean Welleck, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Xiang Ren, Allyson Ettinger, Zaïd Harchaoui, Yejin Choi:
Faith and Fate: Limits of Transformers on Compositionality. - Biagio La Rosa, Leilani Gilpin, Roberto Capobianco:
Towards a fuller understanding of neurons with Clustered Compositional Explanations. - Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Michael Burrows, Charith Mendis, Bryan Perozzi:
TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs. - Zhongzhan Huang, Pan Zhou, Shuicheng Yan, Liang Lin:
ScaleLong: Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection. - Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan, Anil Vullikanti:
Faster approximate subgraph counts with privacy. - Soochan Lee, Jaehyeon Son, Gunhee Kim:
Recasting Continual Learning as Sequence Modeling. - Larry Han, Zhu Shen, José R. Zubizarreta:
Multiply Robust Federated Estimation of Targeted Average Treatment Effects. - Jiale Tao, Shuhang Gu, Wen Li, Lixin Duan:
Learning Motion Refinement for Unsupervised Face Animation. - Feng Wang, Zilong Chen, Guokang Wang, Yafei Song, Huaping Liu:
Masked Space-Time Hash Encoding for Efficient Dynamic Scene Reconstruction. - Lukas Eisenmann, Zahra Monfared, Niclas Alexander Göring, Daniel Durstewitz:
Bifurcations and loss jumps in RNN training. - Aran Nayebi, Rishi Rajalingham, Mehrdad Jazayeri, Guangyu Robert Yang:
Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes. - Jinheng Xie, Kai Ye, Yudong Li, Yuexiang Li, Kevin Qinghong Lin, Yefeng Zheng, Linlin Shen, Mike Zheng Shou:
Learning Visual Prior via Generative Pre-Training. - Louis Serrano, Lise Le Boudec, Armand Kassaï Koupaï, Thomas X. Wang, Yuan Yin, Jean-Noël Vittaut, Patrick Gallinari:
Operator Learning with Neural Fields: Tackling PDEs on General Geometries. - Zhenbo Song, Xianghui Ze, Jianfeng Lu, Yujiao Shi:
Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization. - Ronald Xie, Kuan Pang, Sai Chung, Catia Perciani, Sonya MacParland, Bo Wang, Gary D. Bader:
Spatially Resolved Gene Expression Prediction from Histology Images via Bi-modal Contrastive Learning. - Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David M. Blei:
Causal-structure Driven Augmentations for Text OOD Generalization. - Xiong-Hui Chen, Yang Yu, Zhengmao Zhu, Zhihua Yu, Zhenjun Chen, Chenghe Wang, Yinan Wu, Rong-Jun Qin, Hongqiu Wu, Ruijin Ding, Fangsheng Huang:
Adversarial Counterfactual Environment Model Learning. - Lee Cohen, Yishay Mansour, Michal Moshkovitz:
Finding Safe Zones of Markov Decision Processes Policies. - Sam Adam-Day, Theodor-Mihai Iliant, Ismail Ilkan Ceylan:
Zero-One Laws of Graph Neural Networks. - Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang:
Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective. - Jaskirat Singh, Liang Zheng:
Divide, Evaluate, and Refine: Evaluating and Improving Text-to-Image Alignment with Iterative VQA Feedback. - Yuyang Deng, Mohammad Mahdi Kamani, Pouria Mahdavinia, Mehrdad Mahdavi:
Distributed Personalized Empirical Risk Minimization. - Zhiyu Jin, Xuli Shen, Bin Li, Xiangyang Xue:
Training-free Diffusion Model Adaptation for Variable-Sized Text-to-Image Synthesis. - Bingcong Li, Georgios B. Giannakis:
Enhancing Sharpness-Aware Optimization Through Variance Suppression. - Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang:
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. - Kai Tan, Pierre C. Bellec:
Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions. - Ben Prystawski, Michael Li, Noah D. Goodman:
Why think step by step? Reasoning emerges from the locality of experience. - Yilan Chen, Wei Huang, Hao Wang, Charlotte Loh, Akash Srivastava, Lam M. Nguyen, Lily Weng:
Analyzing Generalization of Neural Networks through Loss Path Kernels. - Shen Jiang, Zipeng Ji, Guanghui Zhu, Chunfeng Yuan, Yihua Huang:
Operation-Level Early Stopping for Robustifying Differentiable NAS. - Muhammad Shah, Aqsa Kashaf, Bhiksha Raj:
Training on Foveated Images Improves Robustness to Adversarial Attacks. - Rishi D. Jha, Jonathan Hayase, Sewoong Oh:
Label Poisoning is All You Need. - Jingwen Fu, Zhizheng Zhang, Dacheng Yin, Yan Lu, Nanning Zheng:
Learning Trajectories are Generalization Indicators. - Chuofan Ma, Yi Jiang, Xin Wen, Zehuan Yuan, Xiaojuan Qi:
CoDet: Co-occurrence Guided Region-Word Alignment for Open-Vocabulary Object Detection. - Alexandre Ramé, Guillaume Couairon, Corentin Dancette, Jean-Baptiste Gaya, Mustafa Shukor, Laure Soulier, Matthieu Cord:
Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards. - Zixing Song, Yifei Zhang, Irwin King:
Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning. - Achraf Azize, Marc Jourdan, Aymen Al Marjani, Debabrota Basu:
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence. - Tiep Le, Vasudev Lal, Phillip Howard:
COCO-Counterfactuals: Automatically Constructed Counterfactual Examples for Image-Text Pairs. - Zelin Ni, Hang Yu, Shizhan Liu, Jianguo Li, Weiyao Lin:
BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis. - Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael W. Mahoney, Amir Gholami:
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. - Shu-Lin Xu, Yifan Sun, Faen Zhang, Anqi Xu, Xiu-Shen Wei, Yi Yang:
Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels. - Vaishnav Potlapalli, Syed Waqas Zamir, Salman H. Khan, Fahad Shahbaz Khan:
PromptIR: Prompting for All-in-One Image Restoration. - James Cook, Milind Shyani, Nina Mishra:
Creating a Public Repository for Joining Private Data. - Tran Phong, Haoran Wu, Cunjun Yu, Panpan Cai, Sifa Zheng, David Hsu:
What Truly Matters in Trajectory Prediction for Autonomous Driving? - Yuancheng Wang, Zeqian Ju, Xu Tan, Lei He, Zhizheng Wu, Jiang Bian, Sheng Zhao:
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models. - Michael Scholkemper, Michael T. Schaub:
An Optimization-based Approach To Node Role Discovery in Networks: Approximating Equitable Partitions. - Xingyu Jiang, Jiayi Ma:
Robust Model Reasoning and Fitting via Dual Sparsity Pursuit. - Jonathan Crabbé, Mihaela van der Schaar:
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance. - Zhi Li, Yifan Liu, Yin Zhang:
Back-Modality: Leveraging Modal Transformation for Data Augmentation. - Alireza Mousavi Hosseini, Denny Wu, Taiji Suzuki, Murat A. Erdogdu:
Gradient-Based Feature Learning under Structured Data. - Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng:
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? - Fanjie Kong, Shuai Yuan, Weituo Hao, Ricardo Henao:
Mitigating Test-Time Bias for Fair Image Retrieval. - Praneeth Kacham, David P. Woodruff:
Lower Bounds on Adaptive Sensing for Matrix Recovery. - Anagh Malik, Parsa Mirdehghan, Sotiris Nousias, Kyros Kutulakos, David B. Lindell:
Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstruction. - Shinji Ito, Kei Takemura:
An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits. - Filippo Maria Bianchi, Veronica Lachi:
The expressive power of pooling in Graph Neural Networks. - Muhammad Akhtar Munir, Salman H. Khan, Muhammad Haris Khan, Mohsen Ali, Fahad Shahbaz Khan:
Cal-DETR: Calibrated Detection Transformer. - Minhak Song, Chulhee Yun:
Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory. - Hugo Laurençon, Lucile Saulnier, Léo Tronchon, Stas Bekman, Amanpreet Singh, Anton Lozhkov, Thomas Wang, Siddharth Karamcheti, Alexander M. Rush, Douwe Kiela, Matthieu Cord, Victor Sanh:
OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents. - Damien Teney, Yong Lin, Seong Joon Oh, Ehsan Abbasnejad:
ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets. - Maria Sofia Bucarelli, Matilde Fjeldsø Larsen, Chris Schwiegelshohn, Mads Toftrup:
On Generalization Bounds for Projective Clustering. - Tianqin Li, Ziqi Wen, Yangfan Li, Tai Sing Lee:
Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity. - Ignacio Hounie, Alejandro Ribeiro, Luiz F. O. Chamon:
Resilient Constrained Learning. - Christian Kümmerle, Johannes Maly:
Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares. - Samuel Lanthaler, Nicholas H. Nelsen:
Error Bounds for Learning with Vector-Valued Random Features. - Yang Cao, Yihan Zeng, Hang Xu, Dan Xu:
CoDA: Collaborative Novel Box Discovery and Cross-modal Alignment for Open-vocabulary 3D Object Detection. - Aahlad Manas Puli, Lily H. Zhang, Yoav Wald, Rajesh Ranganath:
Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy. - Yuandong Tian, Yiping Wang, Beidi Chen, Simon S. Du:
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer. - Congye Wang, Ye Chen, Heishiro Kanagawa, Chris J. Oates:
Stein Π-Importance Sampling. - Rui Yang, Lin Song, Yanwei Li, Sijie Zhao, Yixiao Ge, Xiu Li, Ying Shan:
GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction. - Steven D. Morad, Ryan Kortvelesy, Stephan Liwicki, Amanda Prorok:
Reinforcement Learning with Fast and Forgetful Memory. - Taylor W. Webb, Shanka Subhra Mondal, Jonathan D. Cohen:
Systematic Visual Reasoning through Object-Centric Relational Abstraction. - Leonard Salewski, Stephan Alaniz, Isabel Rio-Torto, Eric Schulz, Zeynep Akata:
In-Context Impersonation Reveals Large Language Models' Strengths and Biases. - Suyash Gupta, Dominik Rothenhäusler:
The s-value: evaluating stability with respect to distributional shifts. - Jaroslaw Blasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran:
When Does Optimizing a Proper Loss Yield Calibration? - Shaohan Huang, Li Dong, Wenhui Wang, Yaru Hao, Saksham Singhal, Shuming Ma, Tengchao Lv, Lei Cui, Owais Khan Mohammed, Barun Patra, Qiang Liu, Kriti Aggarwal, Zewen Chi, Nils Johan Bertil Bjorck, Vishrav Chaudhary, Subhojit Som, Xia Song, Furu Wei:
Language Is Not All You Need: Aligning Perception with Language Models. - Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han:
Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources. - Grégoire Pacreau, Karim Lounici:
Robust covariance estimation with missing values and cell-wise contamination. - Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou:
Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models. - Henry Ling-Hei Tsang, Thomas D. Ahle:
Clustering the Sketch: Dynamic Compression for Embedding Tables. - Xiyuan Yang, Wenke Huang, Mang Ye:
Dynamic Personalized Federated Learning with Adaptive Differential Privacy. - L. Elisa Celis, Amit Kumar, Anay Mehrotra, Nisheeth K. Vishnoi:
Bias in Evaluation Processes: An Optimization-Based Model. - Cuong Tran, Ferdinando Fioretto:
Data Minimization at Inference Time. - Yuanhao Wang, Ramzi Idoughi, Wolfgang Heidrich:
Learning Adaptive Tensorial Density Fields for Clean Cryo-ET Reconstruction. - Kavosh Asadi, Rasool Fakoor, Shoham Sabach:
Resetting the Optimizer in Deep RL: An Empirical Study. - Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh, Quanquan Gu:
Why Does Sharpness-Aware Minimization Generalize Better Than SGD? - Ryoma Yataka, Kazuki Hirashima, Masashi Shiraishi:
Grassmann Manifold Flows for Stable Shape Generation. - Pratik Karmakar, Debabrota Basu:
Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack. - Junfeng Fang, Wei Liu, Yuan Gao, Zemin Liu, An Zhang, Xiang Wang, Xiangnan He:
Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis. - Nika Haghtalab, Michael I. Jordan, Eric Zhao:
A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning. - Emanuele Marconato, Stefano Teso, Antonio Vergari, Andrea Passerini:
Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts. - Xinyuan Cao, Santosh S. Vempala:
Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time. - Fangchen Yu, Runze Zhao, Zhan Shi, Yiwen Lu, Jicong Fan, Yicheng Zeng, Jianfeng Mao, Wenye Li:
Boosting Spectral Clustering on Incomplete Data via Kernel Correction and Affinity Learning. - Qingkai Fang, Yan Zhou, Yang Feng:
DASpeech: Directed Acyclic Transformer for Fast and High-quality Speech-to-Speech Translation. - Jihoon Tack, Subin Kim, Sihyun Yu, Jaeho Lee, Jinwoo Shin, Jonathan Richard Schwarz:
Learning Large-scale Neural Fields via Context Pruned Meta-Learning. - Daiki E. Matsunaga, Jongmin Lee, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, Kee-Eung Kim:
AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation. - Shivani Bathla, Vinita Vasudevan:
Approximate inference of marginals using the IBIA framework. - Ho Man Kwan, Ge Gao, Fan Zhang, Andrew Gower, David Bull:
HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation. - Wenjing Chen, Victoria G. Crawford:
Bicriteria Approximation Algorithms for the Submodular Cover Problem. - Yash Gupta, Runtian Zhai, Arun Sai Suggala, Pradeep Ravikumar:
Responsible AI (RAI) Games and Ensembles. - Rui Feng, Qi Zhu, Huan Tran, Binghong Chen, Aubrey Toland, Rampi Ramprasad, Chao Zhang:
May the Force be with You: Unified Force-Centric Pre-Training for 3D Molecular Conformations. - Hu Yu, Jie Huang, Lingzhi Li, Man Zhou, Feng Zhao:
Deep Fractional Fourier Transform. - Hideaki Kim:
Survival Permanental Processes for Survival Analysis with Time-Varying Covariates. - Sarah Rastegar, Hazel Doughty, Cees Snoek:
Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery. - Matthew Douglas Hoffman, Du Phan, David Dohan, Sholto Douglas, Tuan Anh Le, Aaron Parisi, Pavel Sountsov, Charles Sutton, Sharad Vikram, Rif A. Saurous:
Training Chain-of-Thought via Latent-Variable Inference. - Sihan Chen, Handong Li, Qunbo Wang, Zijia Zhao, Mingzhen Sun, Xinxin Zhu, Jing Liu:
VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset. - Shuyi Li, Michael O'Connor, Shiwei Lan:
Bayesian Learning via Q-Exponential Process. - Huayang Li, Tian Lan, Zihao Fu, Deng Cai, Lemao Liu, Nigel Collier, Taro Watanabe, Yixuan Su:
Repetition In Repetition Out: Towards Understanding Neural Text Degeneration from the Data Perspective. - Fei Deng, Junyeong Park, Sungjin Ahn:
Facing Off World Model Backbones: RNNs, Transformers, and S4. - Kazuki Shimada, Archontis Politis, Parthasaarathy Sudarsanam, Daniel Aleksander Krause, Kengo Uchida, Sharath Adavanne, Aapo Hakala, Yuichiro Koyama, Naoya Takahashi, Shusuke Takahashi, Tuomas Virtanen, Yuki Mitsufuji:
STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events. - Ge Yuan, Xiaodong Cun, Yong Zhang, Maomao Li, Chenyang Qi, Xintao Wang, Ying Shan, Huicheng Zheng:
Inserting Anybody in Diffusion Models via Celeb Basis. - Matthias Minderer, Alexey A. Gritsenko, Neil Houlsby:
Scaling Open-Vocabulary Object Detection. - Pengze Zhang, Hubery Yin, Chen Li, Xiaohua Xie:
Formulating Discrete Probability Flow Through Optimal Transport. - Changmin Yu, Neil Burgess, Maneesh Sahani, Samuel J. Gershman:
Successor-Predecessor Intrinsic Exploration. - Xueyuan Lin, Haihong E, Chengjin Xu, Gengxian Zhou, Haoran Luo, Tianyi Hu, Fenglong Su, Ningyuan Li, Mingzhi Sun:
TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph. - Anand Bhattad, Daniel McKee, Derek Hoiem, David A. Forsyth:
StyleGAN knows Normal, Depth, Albedo, and More. - Lalit Pandey, Samantha M. W. Wood, Justin N. Wood:
Are Vision Transformers More Data Hungry Than Newborn Visual Systems? - Dan Busbridge, Jason Ramapuram, Pierre Ablin, Tatiana Likhomanenko, Eeshan Gunesh Dhekane, Xavier Suau Cuadros, Russell Webb:
How to Scale Your EMA. - Zeyang Zhang, Xin Wang, Ziwei Zhang, Guangyao Shen, Shiqi Shen, Wenwu Zhu:
Unsupervised Graph Neural Architecture Search with Disentangled Self-Supervision. - Ruixiang (Ryan) Tang, Jiayi Yuan, Yiming Li, Zirui Liu, Rui Chen, Xia Hu:
Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots. - Xiwen Wang, Jiaxi Ying, Daniel P. Palomar:
Learning Large-Scale MTP2 Gaussian Graphical Models via Bridge-Block Decomposition. - Subin Kim, Kyungmin Lee, June Suk Choi, Jongheon Jeong, Kihyuk Sohn, Jinwoo Shin:
Collaborative Score Distillation for Consistent Visual Editing. - Irene Wang, Prashant J. Nair, Divya Mahajan:
FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout. - Qizhou Wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han:
Learning to Augment Distributions for Out-of-distribution Detection. - El Mehdi Saad, Gilles Blanchard, Nicolas Verzelen:
Covariance-adaptive best arm identification. - Benedikt Blumenstiel, Johannes Jakubik, Hilde Kühne, Michael Vössing:
What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentation. - Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Simon Reisch, Luise Kärger, Gerhard Neumann:
Swarm Reinforcement Learning for Adaptive Mesh Refinement. - Jianfeng Cai, José Vinícius de Miranda Cardoso, Daniel P. Palomar, Jiaxi Ying:
Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity. - Mo Tiwari, Ryan Kang, Donghyun Lee, Sebastian Thrun, Ilan Shomorony, Martin J. Zhang:
BanditPAM++: Faster k-medoids Clustering. - Maxime Chevalier-Boisvert, Bolun Dai, Mark Towers, Rodrigo Perez-Vicente, Lucas Willems, Salem Lahlou, Suman Pal, Pablo Samuel Castro, Jordan K. Terry:
Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks. - Kang Xu, Chenjia Bai, Xiaoteng Ma, Dong Wang, Bin Zhao, Zhen Wang, Xuelong Li, Wei Li:
Cross-Domain Policy Adaptation via Value-Guided Data Filtering. - Yuhao Mao, Mark Niklas Müller, Marc Fischer, Martin T. Vechev:
Connecting Certified and Adversarial Training. - Akhil Bagaria, Ben Abbatematteo, Omer Gottesman, Matt Corsaro, Sreehari Rammohan, George Dimitri Konidaris:
Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning. - Ilia Sucholutsky, Tom Griffiths:
Alignment with human representations supports robust few-shot learning. - Shuyang Sun, Weijun Wang, Andrew G. Howard, Qihang Yu, Philip H. S. Torr, Liang-Chieh Chen:
ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation. - Kaiwen Wu, Kyurae Kim, Roman Garnett, Jacob R. Gardner:
The Behavior and Convergence of Local Bayesian Optimization. - Junyu Zhang, Daochang Liu, Shichao Zhang, Chang Xu:
Contrastive Sampling Chains in Diffusion Models. - Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin:
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data. - Siyuan Huang, Yunchong Song, Jiayue Zhou, Zhouhan Lin:
Tailoring Self-Attention for Graph via Rooted Subtrees. - Zeyuan Yin, Eric P. Xing, Zhiqiang Shen:
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective. - Tianxiao Li, Hongyu Guo, Filippo Grazioli, Mark Gerstein, Martin Renqiang Min:
Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering. - Yung-Hsuan Lai, Yen-Chun Chen, Frank Wang:
Modality-Independent Teachers Meet Weakly-Supervised Audio-Visual Event Parser. - Fei Zhang, Tianfei Zhou, Boyang Li, Hao He, Chaofan Ma, Tianjiao Zhang, Jiangchao Yao, Ya Zhang, Yanfeng Wang:
Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation. - Han Zhong, Tong Zhang:
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes. - Xiaoying Zhang, Junpu Chen, Hongning Wang, Hong Xie, Yang Liu, John C. S. Lui, Hang Li:
Uncertainty-Aware Instance Reweighting for Off-Policy Learning. - Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard:
Model-free Posterior Sampling via Learning Rate Randomization. - Preetha Vijayan, Prashant Shivaram Bhat, Bahram Zonooz, Elahe Arani:
TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion. - Anshuk Uppal, Kristoffer Stensbo-Smidt, Wouter Boomsma, Jes Frellsen:
Implicit Variational Inference for High-Dimensional Posteriors. - Chenglin Fan, Ping Li, Xiaoyun Li:
k-Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy. - Xingdong Feng, Xin He, Caixing Wang, Chao Wang, Jingnan Zhang:
Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift. - Mathieu Chalvidal, Thomas Serre, Rufin VanRullen:
Learning Functional Transduction. - Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci:
Gaussian Membership Inference Privacy. - Huiwon Jang, Jihoon Tack, Daewon Choi, Jongheon Jeong, Jinwoo Shin:
Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder. - Zhiwei Xu, Bin Zhang, Dapeng Li, Guangchong Zhou, Zeren Zhang, Guoliang Fan:
Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative MARL. - Mintong Kang, Dawn Song, Bo Li:
DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial Purification. - Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic:
Squared Neural Families: A New Class of Tractable Density Models. - Zibo Zhao, Wen Liu, Xin Chen, Xianfang Zeng, Rui Wang, Pei Cheng, Bin Fu, Tao Chen, Gang Yu, Shenghua Gao:
Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation. - Jiaming Qiu, Xiongtao Dai:
Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance. - Wei Chen, Zichen Miao, Qiang Qiu:
Inner Product-based Neural Network Similarity. - Shida Wang, Beichen Xue:
State-space models with layer-wise nonlinearity are universal approximators with exponential decaying memory. - Ankur Sikarwar, Mengmi Zhang:
Decoding the Enigma: Benchmarking Humans and AIs on the Many Facets of Working Memory. - Kazu Ghalamkari, Mahito Sugiyama, Yoshinobu Kawahara:
Many-body Approximation for Non-negative Tensors. - Richeng Jin, Zhonggen Su, Caijun Zhong, Zhaoyang Zhang, Tony Q. S. Quek, Huaiyu Dai:
Breaking the Communication-Privacy-Accuracy Tradeoff with f-Differential Privacy. - Haoran Chen, Xintong Han, Zuxuan Wu, Yu-Gang Jiang:
Multi-Prompt Alignment for Multi-Source Unsupervised Domain Adaptation. - Murat Kocaoglu:
Characterization and Learning of Causal Graphs with Small Conditioning Sets. - Mehrdad Ghadiri, David Arbour, Tung Mai, Cameron Musco, Anup B. Rao:
Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation. - Sungwon Kim, Kevin J. Shih, Rohan Badlani, João Felipe Santos, Evelina Bakhturina, Mikyas Desta, Rafael Valle, Sungroh Yoon, Bryan Catanzaro:
P-Flow: A Fast and Data-Efficient Zero-Shot TTS through Speech Prompting. - Jingfeng Wu, Vladimir Braverman, Jason D. Lee:
Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability. - Junchi Yang, Xiang Li, Ilyas Fatkhullin, Niao He:
Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods. - Zihao Wang, Lei Wu:
Theoretical Analysis of the Inductive Biases in Deep Convolutional Networks. - Xingyu Chen, Weiyao Wang, Hao Tang, Matt Feiszli:
Object Reprojection Error (ORE): Camera pose benchmarks from lightweight tracking annotations. - Samuel Dooley, Rhea Sukthanker, John P. Dickerson, Colin White, Frank Hutter, Micah Goldblum:
Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition. - Yanjie Ze, Yuyao Liu, Ruizhe Shi, Jiaxin Qin, Zhecheng Yuan, Jiashun Wang, Huazhe Xu:
H-InDex: Visual Reinforcement Learning with Hand-Informed Representations for Dexterous Manipulation. - Lazar Atanackovic, Alexander Tong, Bo Wang, Leo J. Lee, Yoshua Bengio, Jason S. Hartford:
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets. - Juanma Zambrano Chaves, Nandita Bhaskhar, Maayane Attias, Jean-Benoit Delbrouck, Daniel L. Rubin, Andreas M. Loening, Curtis P. Langlotz, Akshay Chaudhari:
RaLEs: a Benchmark for Radiology Language Evaluations. - Mohammad Salameh, Keith G. Mills, Negar Hassanpour, Fred X. Han, Shuting Zhang, Wei Lu, Shangling Jui, Chunhua Zhou, Fengyu Sun, Di Niu:
AutoGO: Automated Computation Graph Optimization for Neural Network Evolution. - Zhenting Wang, Chen Chen, Yi Zeng, Lingjuan Lyu, Shiqing Ma:
Where Did I Come From? Origin Attribution of AI-Generated Images. - Dongmin Park, Seola Choi, Doyoung Kim, Hwanjun Song, Jae-Gil Lee:
Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy. - Sebastian Gerard, Yu Zhao, Josephine Sullivan:
WildfireSpreadTS: A dataset of multi-modal time series for wildfire spread prediction. - Weizhi Wang, Li Dong, Hao Cheng, Xiaodong Liu, Xifeng Yan, Jianfeng Gao, Furu Wei:
Augmenting Language Models with Long-Term Memory. - Fabian Jogl, Maximilian Thiessen, Thomas Gärtner:
Expressivity-Preserving GNN Simulation. - Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang, Haifeng Xu:
Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial? - Praveen Venkatesh, Corbett Bennett, Sam Gale, Tamina K. Ramirez, Greggory Heller, Severine Durand, Shawn R. Olsen, Stefan Mihalas:
Gaussian Partial Information Decomposition: Bias Correction and Application to High-dimensional Data. - Zhiyu Zhang, Ashok Cutkosky, Yannis Paschalidis:
Unconstrained Dynamic Regret via Sparse Coding. - Zeshuai Deng, Zhuokun Chen, Shuaicheng Niu, Thomas H. Li, Bohan Zhuang, Mingkui Tan:
Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction. - Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou:
Replicability in Reinforcement Learning. - Leonardo Cotta, Gal Yehuda, Assaf Schuster, Chris J. Maddison:
Probabilistic Invariant Learning with Randomized Linear Classifiers. - Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang:
FedNAR: Federated Optimization with Normalized Annealing Regularization. - Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot, Khyathi Raghavi Chandu, David Wadden, Kelsey MacMillan, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi:
How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources. - Christos Sourmpis, Carl C. H. Petersen, Wulfram Gerstner, Guillaume Bellec:
Trial matching: capturing variability with data-constrained spiking neural networks. - Mengfan Xu, Diego Klabjan:
Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards. - Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, John Rush, Abhradeep Guha Thakurta, Zheng Xu:
(Amplified) Banded Matrix Factorization: A unified approach to private training. - Nora Schneider, Shirin Goshtasbpour, Fernando Pérez-Cruz:
Anchor Data Augmentation. - Ingvar M. Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni:
The noise level in linear regression with dependent data. - Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, Moontae Lee:
SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations. - Miles Turpin, Julian Michael, Ethan Perez, Samuel R. Bowman:
Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting. - Chenxu Zhao, Wei Qian, Rex Ying, Mengdi Huai:
Static and Sequential Malicious Attacks in the Context of Selective Forgetting. - Kanchana Ranasinghe, Michael S. Ryoo:
Language-based Action Concept Spaces Improve Video Self-Supervised Learning. - Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar:
TRIAGE: Characterizing and auditing training data for improved regression. - Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, Aditya Grover:
ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling. - Ziyad Benomar, Vianney Perchet:
Advice Querying under Budget Constraint for Online Algorithms. - Xunhan Hu, Jian Zhao, Wengang Zhou, Ruili Feng, Houqiang Li:
DIFFER: Decomposing Individual Reward for Fair Experience Replay in Multi-Agent Reinforcement Learning. - Yelysei Bondarenko, Markus Nagel, Tijmen Blankevoort:
Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing. - Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki:
Adversarial Training from Mean Field Perspective. - Felix Biggs, Antonin Schrab, Arthur Gretton:
MMD-Fuse: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting. - Zhengdong Hu, Yifan Sun, Jingdong Wang, Yi Yang:
DAC-DETR: Divide the Attention Layers and Conquer. - Sepehr Assadi, Vihan Shah, Chen Wang:
Streaming Algorithms and Lower Bounds for Estimating Correlation Clustering Cost. - Jiayi Shen, Xiantong Zhen, Qi Wang, Marcel Worring:
Episodic Multi-Task Learning with Heterogeneous Neural Processes. - Mher Safaryan, Alexandra Peste, Dan Alistarh:
Knowledge Distillation Performs Partial Variance Reduction. - Zifu Wang, Xuefei Ning, Matthew B. Blaschko:
Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels. - Rui Min, Zeyu Qin, Li Shen, Minhao Cheng:
Towards Stable Backdoor Purification through Feature Shift Tuning. - Tiange Luo, Chris Rockwell, Honglak Lee, Justin Johnson:
Scalable 3D Captioning with Pretrained Models. - Sifan Liu:
Langevin Quasi-Monte Carlo. - Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann:
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting. - Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein:
What Can We Learn from Unlearnable Datasets? - Jiannan Xiang, Tianhua Tao, Yi Gu, Tianmin Shu, Zirui Wang, Zichao Yang, Zhiting Hu:
Language Models Meet World Models: Embodied Experiences Enhance Language Models. - Dayoung Gong, Joonseok Lee, Deunsol Jung, Suha Kwak, Minsu Cho:
Activity Grammars for Temporal Action Segmentation. - Daehyun Kim, Sungyong Baik, Tae Hyun Kim:
SANFlow: Semantic-Aware Normalizing Flow for Anomaly Detection. - Sachin Chauhan, Zeel B. Patel, Sayan Ranu, Rijurekha Sen, Nipun Batra:
AirDelhi: Fine-Grained Spatio-Temporal Particulate Matter Dataset From Delhi For ML based Modeling. - Caleb Dahlke, Jason Pacheco:
On Convergence of Polynomial Approximations to the Gaussian Mixture Entropy. - Jinxin Liu, Li He, Yachen Kang, Zifeng Zhuang, Donglin Wang, Huazhe Xu:
CEIL: Generalized Contextual Imitation Learning. - Nikita Gushchin, Alexander Kolesov, Alexander Korotin, Dmitry P. Vetrov, Evgeny Burnaev:
Entropic Neural Optimal Transport via Diffusion Processes. - Lam M. Nguyen, Trang H. Tran:
On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms. - Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova:
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts. - Sarah Mameche, David Kaltenpoth, Jilles Vreeken:
Learning Causal Models under Independent Changes. - Yihan Wang, Jatin Chauhan, Wei Wang, Cho-Jui Hsieh:
Universality and Limitations of Prompt Tuning. - Yimin Fan, Fahim Dalvi, Nadir Durrani, Hassan Sajjad:
Evaluating Neuron Interpretation Methods of NLP Models. - Jiang-Xin Shi, Tong Wei, Yuke Xiang, Yufeng Li:
How Re-sampling Helps for Long-Tail Learning? - Sarah Schwettmann, Tamar Rott Shaham, Joanna Materzynska, Neil Chowdhury, Shuang Li, Jacob Andreas, David Bau, Antonio Torralba:
FIND: A Function Description Benchmark for Evaluating Interpretability Methods. - Hao Tang, Kevin J. Liang, Kristen Grauman, Matt Feiszli, Weiyao Wang:
EgoTracks: A Long-term Egocentric Visual Object Tracking Dataset. - Andrew F. Luo, Margaret M. Henderson, Leila Wehbe, Michael J. Tarr:
Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models. - Jinghua Hou, Zhe Liu, Dingkang Liang, Zhikang Zou, Xiaoqing Ye, Xiang Bai:
Query-based Temporal Fusion with Explicit Motion for 3D Object Detection. - Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli:
Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection. - Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman:
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. - Haoyu Guo, Sida Peng, Yunzhi Yan, Linzhan Mou, Yujun Shen, Hujun Bao, Xiaowei Zhou:
Compact Neural Volumetric Video Representations with Dynamic Codebooks. - Runnan Chen, Youquan Liu, Lingdong Kong, Nenglun Chen, Xinge Zhu, Yuexin Ma, Tongliang Liu, Wenping Wang:
Towards Label-free Scene Understanding by Vision Foundation Models. - Vladimir Feinberg, Xinyi Chen, Y. Jennifer Sun, Rohan Anil, Elad Hazan:
Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions. - Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi Abdelwahed, Hugo Larochelle, David Rolnick:
SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data. - Ruihang Chu, Enze Xie, Shentong Mo, Zhenguo Li, Matthias Nießner, Chi-Wing Fu, Jiaya Jia:
DiffComplete: Diffusion-based Generative 3D Shape Completion. - Yuhao Wang, Enlu Zhou:
Bayesian Risk-Averse Q-Learning with Streaming Observations. - Karthik Valmeekam, Matthew Marquez, Sarath Sreedharan, Subbarao Kambhampati:
On the Planning Abilities of Large Language Models - A Critical Investigation. - Yuanhao Wang, Qinghua Liu, Chi Jin:
Is RLHF More Difficult than Standard RL? A Theoretical Perspective. - Michael Hanna, Ollie Liu, Alexandre Variengien:
How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model. - Varun Jampani, Kevis-Kokitsi Maninis, Andreas Engelhardt, Arjun Karpur, Karen Truong, Kyle Sargent, Stefan Popov, André Araújo, Ricardo Martin-Brualla, Kaushal Patel, Daniel Vlasic, Vittorio Ferrari, Ameesh Makadia, Ce Liu, Yuanzhen Li, Howard Zhou:
NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations. - Jia-Xing Zhong, Ta Ying Cheng, Yuhang He, Kai Lu, Kaichen Zhou, Andrew Markham, Niki Trigoni:
Multi-body SE(3) Equivariance for Unsupervised Rigid Segmentation and Motion Estimation. - Fuqi Jia, Yuhang Dong, Minghao Liu, Pei Huang, Feifei Ma, Jian Zhang:
Suggesting Variable Order for Cylindrical Algebraic Decomposition via Reinforcement Learning. - Mingzhen Sun, Weining Wang, Zihan Qin, Jiahui Sun, Sihan Chen, Jing Liu:
GLOBER: Coherent Non-autoregressive Video Generation via GLOBal Guided Video DecodER. - Sivan Doveh, Assaf Arbelle, Sivan Harary, Roei Herzig, Donghyun Kim, Paola Cascante-Bonilla, Amit Alfassy, Rameswar Panda, Raja Giryes, Rogério Feris, Shimon Ullman, Leonid Karlinsky:
Dense and Aligned Captions (DAC) Promote Compositional Reasoning in VL Models. - Sebastian Zeng, Florian Graf, Roland Kwitt:
Latent SDEs on Homogeneous Spaces. - Yufan Li, Jialiang Mao, Iavor Bojinov:
Balancing Risk and Reward: A Batched-Bandit Strategy for Automated Phased Release. - Xixi Jia, Hailin Wang, Jiangjun Peng, Xiangchu Feng, Deyu Meng:
Preconditioning Matters: Fast Global Convergence of Non-convex Matrix Factorization via Scaled Gradient Descent. - Botao Wang, Jia Li, Yang Liu, Jiashun Cheng, Yu Rong, Wenjia Wang, Fugee Tsung:
Deep Insights into Noisy Pseudo Labeling on Graph Data. - Jeffrey Ouyang-Zhang, Daniel Jesus Diaz, Adam R. Klivans, Philipp Krähenbühl:
Predicting a Protein's Stability under a Million Mutations. - Fiona Lippert, Bart Kranstauber, Emiel van Loon, Patrick Forré:
Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems. - Amit Daniely, Nati Srebro, Gal Vardi:
Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy. - Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa:
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning. - Aniket Rege, Aditya Kusupati, Sharan Ranjit S, Alan Fan, Qingqing Cao, Sham M. Kakade, Prateek Jain, Ali Farhadi:
AdANNS: A Framework for Adaptive Semantic Search. - Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, Vishak Prasad C., Ganesh Ramakrishnan, Micah Goldblum, Colin White:
When Do Neural Nets Outperform Boosted Trees on Tabular Data? - Zhongzheng Xiong, Xiaoyi Zhu, Zengfeng Huang:
Adversarially Robust Distributed Count Tracking via Partial Differential Privacy. - Geon Yeong Park, Jeongsol Kim, Beomsu Kim, Sang Wan Lee, Jong Chul Ye:
Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models. - Aleksandr Pak, Justin Ko, Florent Krzakala:
Optimal Algorithms for the Inhomogeneous Spiked Wigner Model. - Jianwei Zhang, Suren Jayasuriya, Visar Berisha:
Learning Repeatable Speech Embeddings Using An Intra-class Correlation Regularizer. - Ilyas Fatkhullin, Alexander Tyurin, Peter Richtárik:
Momentum Provably Improves Error Feedback! - Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini:
Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes. - Weijian Luo, Tianyang Hu, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhihua Zhang:
Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models. - Jingyuan Xu, Weiwei Liu:
Characterization of Overfitting in Robust Multiclass Classification. - Yifan Zhang, Daquan Zhou, Bryan Hooi, Kai Wang, Jiashi Feng:
Expanding Small-Scale Datasets with Guided Imagination. - Can Chen, Christopher Beckham, Zixuan Liu, Xue (Steve) Liu, Chris Pal:
Parallel-mentoring for Offline Model-based Optimization. - Chih-Yu Lai, Fan-Keng Sun, Zhengqi Gao, Jeffrey H. Lang, Duane S. Boning:
Nominality Score Conditioned Time Series Anomaly Detection by Point/Sequential Reconstruction. - Kun Yi, Qi Zhang, Wei Fan, Shoujin Wang, Pengyang Wang, Hui He, Ning An, Defu Lian, Longbing Cao, Zhendong Niu:
Frequency-domain MLPs are More Effective Learners in Time Series Forecasting. - Yanjing Li, Sheng Xu, Xianbin Cao, Xiao Sun, Baochang Zhang:
Q-DM: An Efficient Low-bit Quantized Diffusion Model. - Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada:
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence. - Cenk Baykal, Dylan J. Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang:
Alternating Updates for Efficient Transformers. - Sangwoo Seo, Sungwon Kim, Chanyoung Park:
Interpretable Prototype-based Graph Information Bottleneck. - Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal:
Self-Chained Image-Language Model for Video Localization and Question Answering. - Wojciech Masarczyk, Mateusz Ostaszewski, Ehsan Imani, Razvan Pascanu, Piotr Milos, Tomasz Trzcinski:
The Tunnel Effect: Building Data Representations in Deep Neural Networks. - Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi S. Jaakkola:
Restart Sampling for Improving Generative Processes. - Xi Yu, Xiang Gu, Haozhi Liu, Jian Sun:
Constructing Non-isotropic Gaussian Diffusion Model Using Isotropic Gaussian Diffusion Model for Image Editing. - Haonan Duan, Adam Dziedzic, Nicolas Papernot, Franziska Boenisch:
Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models. - Quang Nguyen, Truong Vu, Anh Tran, Khoi Nguyen:
Dataset Diffusion: Diffusion-based Synthetic Data Generation for Pixel-Level Semantic Segmentation. - Aashaka Desai, Lauren Berger, Fyodor Minakov, Nessa Milano, Chinmay Singh, Kriston Pumphrey, Richard E. Ladner, Hal Daumé III, Alex X. Lu, Naomi Caselli, Danielle Bragg:
ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition. - Rui Wang, Peipei Li, Huaibo Huang, Chunshui Cao, Ran He, Zhaofeng He:
Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classification. - Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Yuanqi Du, Samuel Stanton, Gary Tom, Bojana Rankovic, Arian Rokkum Jamasb, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Peter Dürholt, Saudamini Chaurasia, Ji Won Park, Felix Strieth-Kalthoff, Alpha A. Lee, Bingqing Cheng, Alán Aspuru-Guzik, Philippe Schwaller, Jian Tang:
GAUCHE: A Library for Gaussian Processes in Chemistry. - Joowon Lee, Hanbaek Lyu, Weixin Yao:
Exponentially Convergent Algorithms for Supervised Matrix Factorization. - Fangzhou Lin, Yun Yue, Ziming Zhang, Songlin Hou, Kazunori D. Yamada, Vijaya Kolachalama, Venkatesh Saligrama:
InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion. - Jack Jewson, Sahra Ghalebikesabi, Chris C. Holmes:
Differentially Private Statistical Inference through β-Divergence One Posterior Sampling. - Yuankun Jiang, Nuowen Kan, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong:
Doubly Robust Augmented Transfer for Meta-Reinforcement Learning. - Cunxiang Wang, Sirui Cheng, Qipeng Guo, Yuanhao Yue, Bowen Ding, Zhikun Xu, Yidong Wang, Xiangkun Hu, Zheng Zhang, Yue Zhang:
Evaluating Open-QA Evaluation. - Zun Wang, Guoqing Liu, Yichi Zhou, Tong Wang, Bin Shao:
Efficiently incorporating quintuple interactions into geometric deep learning force fields. - Stefan Stojanovic, Yassir Jedra, Alexandre Proutière:
Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement Learning. - Balhae Kim, Hyungi Lee, Juho Lee:
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks. - Jérôme Bolte, Edouard Pauwels, Samuel Vaiter:
One-step differentiation of iterative algorithms. - Anish Agarwal, Keegan Harris, Justin Whitehouse, Zhiwei Steven Wu:
Adaptive Principal Component Regression with Applications to Panel Data. - Jiyoung Lee, Seungho Kim, Seunghyun Won, Joonseok Lee, Marzyeh Ghassemi, James Thorne, Jaeseok Choi, O.-Kil Kwon, Edward Choi:
VisAlign: Dataset for Measuring the Alignment between AI and Humans in Visual Perception. - Shuyue Hu, Harold Soh, Georgios Piliouras:
The Best of Both Worlds in Network Population Games: Reaching Consensus and Convergence to Equilibrium. - Zheng Chang, Shuchen Weng, Peixuan Zhang, Yu Li, Si Li, Boxin Shi:
L-CAD: Language-based Colorization with Any-level Descriptions using Diffusion Priors. - Bogdan Raonic, Roberto Molinaro, Tim De Ryck, Tobias Rohner, Francesca Bartolucci, Rima Alaifari, Siddhartha Mishra, Emmanuel de Bézenac:
Convolutional Neural Operators for robust and accurate learning of PDEs. - Kelsey Lieberman, James Diffenderfer, Charles Godfrey, Bhavya Kailkhura:
Neural Image Compression: Generalization, Robustness, and Spectral Biases. - Giacomo Meanti, Antoine Chatalic, Vladimir Kostic, Pietro Novelli, Massimiliano Pontil, Lorenzo Rosasco:
Estimating Koopman operators with sketching to provably learn large scale dynamical systems. - Chengxu Zuo, Jiawei Fang, Shihui Guo, Yipeng Qin:
Self-Adaptive Motion Tracking against On-body Displacement of Flexible Sensors. - Jianzhun Shao, Yun Qu, Chen Chen, Hongchang Zhang, Xiangyang Ji:
Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement Learning. - Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer:
Black-Box Differential Privacy for Interactive ML. - Deepali Jain, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan:
Mnemosyne: Learning to Train Transformers with Transformers. - Yuanqi Du, Yingheng Wang, Yining Huang, Jianan Canal Li, Yanqiao Zhu, Tian Xie, Chenru Duan, John M. Gregoire, Carla Pedro Gomes:
M2Hub: Unlocking the Potential of Machine Learning for Materials Discovery. - Timothy F. Truong Jr., Tristan Bepler:
PoET: A generative model of protein families as sequences-of-sequences. - Darko Drakulic, Sofia Michel, Florian Mai, Arnaud Sors, Jean-Marc Andreoli:
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial Optimization. - Wai Tong Chung, Bassem Akoush, Pushan Sharma, Alex Tamkin, Ki Sung Jung, Jacqueline Chen, Jack Guo, Davy Brouzet, Mohsen Talei, Bruno Savard, Alexei Y. Poludnenko, Matthias Ihme:
Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data. - Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn:
Neural Functional Transformers. - Jiaqi Guan, Xingang Peng, Peiqi Jiang, Yunan Luo, Jian Peng, Jianzhu Ma:
LinkerNet: Fragment Poses and Linker Co-Design with 3D Equivariant Diffusion. - Marc Rigter, Bruno Lacerda, Nick Hawes:
One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning. - Daniel Y. Fu, Simran Arora, Jessica Grogan, Isys Johnson, Evan Sabri Eyuboglu, Armin W. Thomas, Benjamin Spector, Michael Poli, Atri Rudra, Christopher Ré:
Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture. - Yizi Zhang, Tianxiao He, Julien Boussard, Charles Windolf, Olivier Winter, Eric Trautmann, Noam Roth, Hailey Barrell, Mark Churchland, Nicholas A Steinmetz, Erdem Varol, Cole L. Hurwitz, Liam Paninski:
Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes. - Shuchen Xue, Mingyang Yi, Weijian Luo, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma:
SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models. - Wentao Zhu, Jason Qin, Yuke Lou, Hang Ye, Xiaoxuan Ma, Hai Ci, Yizhou Wang:
Social Motion Prediction with Cognitive Hierarchies. - David Durfee:
Unbounded Differentially Private Quantile and Maximum Estimation. - Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari:
How to Turn Your Knowledge Graph Embeddings into Generative Models. - Zikai Xiao, Zihan Chen, Songshang Liu, Hualiang Wang, Yang Feng, Jin Hao, Joey Tianyi Zhou, Jian Wu, Howard H. Yang, Zuozhu Liu:
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer. - Taiki Miyanishi, Fumiya Kitamori, Shuhei Kurita, Jungdae Lee, Motoaki Kawanabe, Nakamasa Inoue:
CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data. - Mingjian Zhu, Hanting Chen, Qiangyu Yan, Xudong Huang, Guanyu Lin, Wei Li, Zhijun Tu, Hailin Hu, Jie Hu, Yunhe Wang:
GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image. - Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi:
On Differentially Private Sampling from Gaussian and Product Distributions. - Sanja Scepanovic, Ivica Obadic, Sagar Joglekar, Laura Giustarini, Cristiano Nattero, Daniele Quercia, Xiaoxiang Zhu:
MedSat: A Public Health Dataset for England Featuring Medical Prescriptions and Satellite Imagery. - Jianyi Yang, Pengfei Li, Tongxin Li, Adam Wierman, Shaolei Ren:
Anytime-Competitive Reinforcement Learning with Policy Prior. - Zhengxin Zhang, Yucheng Huang, Guanglin Duan, Qing Li, Dan Zhao, Yong Jiang, Lianbo Ma, Xi Xiao, Hengyang Xu:
Metis: Understanding and Enhancing In-Network Regular Expressions. - Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He:
Adaptive Test-Time Personalization for Federated Learning. - Chung-Wei Lee, Qinghua Liu, Yasin Abbasi-Yadkori, Chi Jin, Tor Lattimore, Csaba Szepesvári:
Context-lumpable stochastic bandits. - Yuheng Zha, Yichi Yang, Ruichen Li, Zhiting Hu:
Text Alignment Is An Efficient Unified Model for Massive NLP Tasks. - Zhenghao Mark Peng, Wenjie Mo, Chenda Duan, Quanyi Li, Bolei Zhou:
Learning from Active Human Involvement through Proxy Value Propagation. - Vishal Asnani, Abhinav Kumar, Suya You, Xiaoming Liu:
PrObeD: Proactive Object Detection Wrapper. - Anirudhan Badrinath, Yannis Flet-Berliac, Allen Nie, Emma Brunskill:
Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets. - Berfin Simsek, Amire Bendjeddou, Wulfram Gerstner, Johanni Brea:
Should Under-parameterized Student Networks Copy or Average Teacher Weights? - Sapna Chaudhary, Mukulika Maity, Sandip Chakraborty, Naval Kumar Shukla:
A Dataset for Analyzing Streaming Media Performance over HTTP/3 Browsers. - Lingchen Meng, Xiyang Dai, Jianwei Yang, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Yi-Ling Chen, Zuxuan Wu, Lu Yuan, Yu-Gang Jiang:
Learning from Rich Semantics and Coarse Locations for Long-tailed Object Detection. - Emanuele Bugliarello, H. Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender:
StoryBench: A Multifaceted Benchmark for Continuous Story Visualization. - Marco Aversa, Gabriel Nobis, Miriam Hägele, Kai Standvoss, Mihaela Chirica, Roderick Murray-Smith, Ahmed M. Alaa, Lukas Ruff, Daniela Ivanova, Wojciech Samek, Frederick Klauschen, Bruno Sanguinetti, Luis Oala:
DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology. - Yushi Bai, Jiahao Ying, Yixin Cao, Xin Lv, Yuze He, Xiaozhi Wang, Jifan Yu, Kaisheng Zeng, Yijia Xiao, Haozhe Lyu, Jiayin Zhang, Juanzi Li, Lei Hou:
Benchmarking Foundation Models with Language-Model-as-an-Examiner. - Jacek Dmochowski:
Granger Components Analysis: Unsupervised learning of latent temporal dependencies. - Michael Painter, Mohamed Baioumy, Nick Hawes, Bruno Lacerda:
Monte Carlo Tree Search with Boltzmann Exploration. - Alexandre Blain, Bertrand Thirion, Olivier Grisel, Pierre Neuvial:
False Discovery Proportion control for aggregated Knockoffs. - Zhengxuan Wu, Atticus Geiger, Thomas Icard, Christopher Potts, Noah D. Goodman:
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca. - Danyang Zhang, Lu Chen, Situo Zhang, Hongshen Xu, Zihan Zhao, Kai Yu:
Large Language Models Are Semi-Parametric Reinforcement Learning Agents. - Chaoqi Yang, M. Brandon Westover, Jimeng Sun:
BIOT: Biosignal Transformer for Cross-data Learning in the Wild. - Jiaxin Zhang, Zhuohang Li, Kamalika Das, Kumar Sricharan:
Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision. - J. Emmanuel Johnson, Quentin Febvre, Anastasiia Gorbunova, Sammy Metref, Maxime Ballarotta, Julien Le Sommer, Ronan Fablet:
OceanBench: The Sea Surface Height Edition. - Kevin Course, Prasanth B. Nair:
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs. - Ye Zhu, Yu Wu, Zhiwei Deng, Olga Russakovsky, Yan Yan:
Boundary Guided Learning-Free Semantic Control with Diffusion Models. - Morris Alper, Hadar Averbuch-Elor:
Kiki or Bouba? Sound Symbolism in Vision-and-Language Models. - Allen Nie, Yuhui Zhang, Atharva Amdekar, Chris Piech, Tatsunori B. Hashimoto, Tobias Gerstenberg:
MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks. - Zhe Zeng, Guy Van den Broeck:
Collapsed Inference for Bayesian Deep Learning. - Yifan Hu, Jie Wang, Yao Xie, Andreas Krause, Daniel Kuhn:
Contextual Stochastic Bilevel Optimization. - Xiang Zhuang, Qiang Zhang, Keyan Ding, Yatao Bian, Xiao Wang, Jingsong Lv, Hongyang Chen, Huajun Chen:
Learning Invariant Molecular Representation in Latent Discrete Space. - An T. Le, Georgia Chalvatzaki, Armin Biess, Jan Peters:
Accelerating Motion Planning via Optimal Transport. - Yongxin Shi, Chongyu Liu, Dezhi Peng, Cheng Jian, Jiarong Huang, Lianwen Jin:
M5HisDoc: A Large-scale Multi-style Chinese Historical Document Analysis Benchmark. - Rakshith Sharma Srinivasa, Jaejin Cho, Chouchang Yang, Yashas Malur Saidutta, Ching Hua Lee, Yilin Shen, Hongxia Jin:
CWCL: Cross-Modal Transfer with Continuously Weighted Contrastive Loss. - Zikang Tian, Ruizhi Chen, Xing Hu, Ling Li, Rui Zhang, Fan Wu, Shaohui Peng, Jiaming Guo, Zidong Du, Qi Guo, Yunji Chen:
Decompose a Task into Generalizable Subtasks in Multi-Agent Reinforcement Learning. - Victor Boone, Panayotis Mertikopoulos:
The Equivalence of Dynamic and Strategic Stability under Regularized Learning in Games. - Xingbo Du, Chonghua Wang, Ruizhe Zhong, Junchi Yan:
HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection. - Xiaotong Yuan, Ping Li:
L2-Uniform Stability of Randomized Learning Algorithms: Sharper Generalization Bounds and Confidence Boosting. - Xingsi Dong, Si Wu:
Neural Sampling in Hierarchical Exponential-family Energy-based Models. - Weijie Gan, Shirin Shoushtari, Yuyang Hu, Jiaming Liu, Hongyu An, Ulugbek Kamilov:
Block Coordinate Plug-and-Play Methods for Blind Inverse Problems. - Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang:
PreDiff: Precipitation Nowcasting with Latent Diffusion Models. - Liyao Tang, Zhe Chen, Shanshan Zhao, Chaoyue Wang, Dacheng Tao:
All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation. - Hao Dong, Ismail Nejjar, Han Sun, Eleni N. Chatzi, Olga Fink:
SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization. - Jamie Hayes, Borja Balle, Saeed Mahloujifar:
Bounding training data reconstruction in DP-SGD. - Kaiyi Huang, Kaiyue Sun, Enze Xie, Zhenguo Li, Xihui Liu:
T2I-CompBench: A Comprehensive Benchmark for Open-world Compositional Text-to-image Generation. - Huafeng Liu, Liping Jing, Jian Yu:
Neural Processes with Stability. - Anh Do, Thanh Nguyen-Tang, Raman Arora:
Multi-Agent Learning with Heterogeneous Linear Contextual Bandits. - Pierre-Étienne H. Fiquet, Eero P. Simoncelli:
A polar prediction model for learning to represent visual transformations. - Lili Yu, Daniel Simig, Colin Flaherty, Armen Aghajanyan, Luke Zettlemoyer, Mike Lewis:
MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers. - Seungjae Lee, Daesol Cho, Jonghae Park, H. Jin Kim:
CQM: Curriculum Reinforcement Learning with a Quantized World Model. - Lie He, Shiva Prasad Kasiviswanathan:
Debiasing Conditional Stochastic Optimization. - Dairui Wang, Junyu Cao, Yan Zhang, Wei Qi:
Cascading Bandits: Optimizing Recommendation Frequency in Delayed Feedback Environments. - Wenxuan Zeng, Meng Li, Haichuan Yang, Wen-jie Lu, Runsheng Wang, Ru Huang:
CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference. - Pratik Patil, Jin-Hong Du:
Generalized equivalences between subsampling and ridge regularization. - Jialin Chen, Shirley Wu, Abhijit Gupta, Rex Ying:
D4Explainer: In-distribution Explanations of Graph Neural Network via Discrete Denoising Diffusion. - Sepideh Mahabadi, Stojan Trajanovski:
Core-sets for Fair and Diverse Data Summarization. - Eric Balkanski, Noémie Périvier, Clifford Stein, Hao-Ting Wei:
Energy-Efficient Scheduling with Predictions. - Lisa Dunlap, Alyssa Umino, Han Zhang, Jiezhi Yang, Joseph E. Gonzalez, Trevor Darrell:
Diversify Your Vision Datasets with Automatic Diffusion-based Augmentation. - Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai:
DISCS: A Benchmark for Discrete Sampling. - Amin Ghiasi, Ali Shafahi, Reza Ardekani:
Improving Robustness with Adaptive Weight Decay. - Lin Guan, Karthik Valmeekam, Sarath Sreedharan, Subbarao Kambhampati:
Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning. - Chi Xie, Zhao Zhang, Yixuan Wu, Feng Zhu, Rui Zhao, Shuang Liang:
Described Object Detection: Liberating Object Detection with Flexible Expressions. - Daniel Thuerck, Boro Sofranac, Marc E. Pfetsch, Sebastian Pokutta:
Learning Cuts via Enumeration Oracles. - Zihao Yue, Anwen Hu, Liang Zhang, Qin Jin:
Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation. - Hassan Akbari, Dan Kondratyuk, Yin Cui, Rachel Hornung, Huisheng Wang, Hartwig Adam:
Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception. - Guilherme Penedo, Quentin Malartic, Daniel Hesslow, Ruxandra Cojocaru, Hamza Alobeidli, Alessandro Cappelli, Baptiste Pannier, Ebtesam Almazrouei, Julien Launay:
The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data Only. - Carl Hvarfner, Erik Hellsten, Frank Hutter, Luigi Nardi:
Self-Correcting Bayesian Optimization through Bayesian Active Learning. - Laurence I. Midgley, Vincent Stimper, Javier Antorán, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato:
SE(3) Equivariant Augmented Coupling Flows. - Zhimin Chen, Longlong Jing, Yingwei Li, Bing Li:
Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models. - Shengqiong Wu, Hao Fei, Hanwang Zhang, Tat-Seng Chua:
Imagine That! Abstract-to-Intricate Text-to-Image Synthesis with Scene Graph Hallucination Diffusion. - Yifeng Chu, Maxim Raginsky:
A unified framework for information-theoretic generalization bounds. - Wesley Khademi, Fuxin Li:
Diverse Shape Completion via Style Modulated Generative Adversarial Networks. - Lucas Gnecco Heredia, Muni Sreenivas Pydi, Laurent Meunier, Benjamin Négrevergne, Yann Chevaleyre:
On the Role of Randomization in Adversarially Robust Classification. - Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf:
Controlling Text-to-Image Diffusion by Orthogonal Finetuning. - Joshua Horacsek, Usman R. Alim:
NCDL: A Framework for Deep Learning on non-Cartesian Lattices. - Jacob Granley, Tristan Fauvel, Matthew Chalk, Michael Beyeler:
Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual Prostheses. - Dongho Lee, Jongseo Lee, Jinwoo Choi:
CAST: Cross-Attention in Space and Time for Video Action Recognition. - Arun Ganesh, Mahdi Haghifam, Thomas Steinke, Abhradeep Guha Thakurta:
Faster Differentially Private Convex Optimization via Second-Order Methods. - Rohan Alur, Loren Laine, Darrick K. Li, Manish Raghavan, Devavrat Shah, Dennis L. Shung:
Auditing for Human Expertise. - Sergey Pozdnyakov, Michele Ceriotti:
Smooth, exact rotational symmetrization for deep learning on point clouds. - Matthew Farrugia-Roberts:
Functional Equivalence and Path Connectivity of Reducible Hyperbolic Tangent Networks. - David P. Woodruff, Fred Zhang, Samson Zhou:
On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds. - Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Bernd Ensing, Max Welling:
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths. - Yeqi Bai, Ben Fei, Youquan Liu, Tao Ma, Yuenan Hou, Botian Shi, Yikang Li:
RangePerception: Taming LiDAR Range View for Efficient and Accurate 3D Object Detection. - Zhiwei Hao, Jianyuan Guo, Kai Han, Yehui Tang, Han Hu, Yunhe Wang, Chang Xu:
One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation. - Lee M. Gunderson, Gecia Bravo Hermsdorff, Peter Orbanz:
The Graph Pencil Method: Mapping Subgraph Densities to Stochastic Block Models. - Zihan Luo, Hong Huang, Jianxun Lian, Xiran Song, Xing Xie, Hai Jin:
Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective. - Chris Lin, Ian Covert, Su-In Lee:
On the Robustness of Removal-Based Feature Attributions. - Yiheng Zhu, Jialu Wu, Chaowen Hu, Jiahuan Yan, Chang-Yu Hsieh, Tingjun Hou, Jian Wu:
Sample-efficient Multi-objective Molecular Optimization with GFlowNets. - Rong Wang, Wei Mao, Hongdong Li:
DeepSimHO: Stable Pose Estimation for Hand-Object Interaction via Physics Simulation. - Jing Xu, Jiaye Teng, Yang Yuan, Andrew C. Yao:
Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression. - Jinhui Hou, Zhiyu Zhu, Junhui Hou, Hui Liu, Huanqiang Zeng, Hui Yuan:
Global Structure-Aware Diffusion Process for Low-light Image Enhancement. - Yuhang Yao, Weizhao Jin, Srivatsan Ravi, Carlee Joe-Wong:
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks. - Mengyu Wang, Henghui Ding, Jun Hao Liew, Jiajun Liu, Yao Zhao, Yunchao Wei:
SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process. - Pablo Moreno-Muñoz, Pol Garcia Recasens, Søren Hauberg:
On Masked Pre-training and the Marginal Likelihood. - Mononito Goswami, Vedant Sanil, Arjun Choudhry, Arvind Srinivasan, Chalisa Udompanyawit, Artur Dubrawski:
AQuA: A Benchmarking Tool for Label Quality Assessment. - Alankrita Bhatt, Nika Haghtalab, Abhishek Shetty:
Smoothed Analysis of Sequential Probability Assignment. - Mengyue Yang, Yonggang Zhang, Zhen Fang, Yali Du, Furui Liu, Jean-Francois Ton, Jianhong Wang, Jun Wang:
Invariant Learning via Probability of Sufficient and Necessary Causes. - Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee:
Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. - Moran Barenboim, Vadim Indelman:
Online POMDP Planning with Anytime Deterministic Guarantees. - Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi:
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model. - Keegan Harris, Chara Podimata, Zhiwei Steven Wu:
Strategic Apple Tasting. - Jinggang Chen, Junjie Li, Xiaoyang Qu, Jianzong Wang, Jiguang Wan, Jing Xiao:
GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection. - Yishi Xu, Jianqiao Sun, Yudi Su, Xinyang Liu, Zhibin Duan, Bo Chen, Mingyuan Zhou:
Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes. - Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster:
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. - Bo Jiang, Ya-Feng Liu:
A Riemannian Exponential Augmented Lagrangian Method for Computing the Projection Robust Wasserstein Distance. - Yunkai Gao, Rui Zhang, Jiaming Guo, Fan Wu, Qi Yi, Shaohui Peng, Siming Lan, Ruizhi Chen, Zidong Du, Xing Hu, Qi Guo, Ling Li, Yunji Chen:
Context Shift Reduction for Offline Meta-Reinforcement Learning. - Hoang Pham, The-Anh Ta, Shiwei Liu, Lichuan Xiang, Dung Le, Hongkai Wen, Long Tran-Thanh:
Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask? - Maria-Florina Balcan, Anh Nguyen, Dravyansh Sharma:
New Bounds for Hyperparameter Tuning of Regression Problems Across Instances. - Alexander Wei, Nika Haghtalab, Jacob Steinhardt:
Jailbroken: How Does LLM Safety Training Fail? - Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah Hanna, Stefano V. Albrecht:
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning. - Duligur Ibeling, Thomas Icard:
Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions. - Shangyuan Liu, Linglingzhi Zhu, Anthony Man-Cho So:
LogSpecT: Feasible Graph Learning Model from Stationary Signals with Recovery Guarantees. - Wonhyeok Choi, Mingyu Shin, Sunghoon Im:
Depth-discriminative Metric Learning for Monocular 3D Object Detection. - Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Joshua M. Susskind, Navdeep Jaitly:
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model. - Richard Gao, Michael Deistler, Jakob H. Macke:
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation. - Guy Blanc, Jane Lange, Chirag Pabbaraju, Colin Sullivan, Li-Yang Tan, Mo Tiwari:
Harnessing the power of choices in decision tree learning. - Tam Nguyen, Tan Nguyen, Richard G. Baraniuk:
Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals. - Alireza Fathollah Pour, Hassan Ashtiani:
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences. - Suhas Kotha, Christopher Brix, J. Zico Kolter, Krishnamurthy Dvijotham, Huan Zhang:
Provably Bounding Neural Network Preimages. - Aaron Lou, Minkai Xu, Adam Farris, Stefano Ermon:
Scaling Riemannian Diffusion Models. - Siyan Zhao, Aditya Grover:
Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models. - Jiankai Sun, Yiqi Jiang, Jianing Qiu, Parth Nobel, Mykel J. Kochenderfer, Mac Schwager:
Conformal Prediction for Uncertainty-Aware Planning with Diffusion Dynamics Model. - Dor Tsur, Ziv Goldfeld, Kristjan H. Greenewald:
Max-Sliced Mutual Information. - Joel Ye, Jennifer L. Collinger, Leila Wehbe, Robert Gaunt:
Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity. - Suneel Belkhale, Yuchen Cui, Dorsa Sadigh:
Data Quality in Imitation Learning. - Jameel Abdul Samadh, Hanan Gani, Noor Hussein, Muhammad Uzair Khattak, Muzammal Naseer, Fahad Shahbaz Khan, Salman H. Khan:
Align Your Prompts: Test-Time Prompting with Distribution Alignment for Zero-Shot Generalization. - Songtao Lu:
SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization. - Xin Shen, Shaozu Yuan, Hongwei Sheng, Heming Du, Xin Yu:
Auslan-Daily: Australian Sign Language Translation for Daily Communication and News. - Stephen Casper, Tong Bu, Yuxiao Li, Jiawei Li, Kevin Zhang, Kaivalya Hariharan, Dylan Hadfield-Menell:
Red Teaming Deep Neural Networks with Feature Synthesis Tools. - Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou:
Rehearsal Learning for Avoiding Undesired Future. - Yan Sun, Li Shen, Dacheng Tao:
Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization. - Dogyoon Song, Kyunghee Han:
Errors-in-variables Fr\'echet Regression with Low-rank Covariate Approximation. - Hao Zheng, Hongming Li, Yong Fan:
Coupled Reconstruction of Cortical Surfaces by Diffeomorphic Mesh Deformation. - Yifang Chen, Yingbing Huang, Simon S. Du, Kevin G. Jamieson, Guanya Shi:
Active representation learning for general task space with applications in robotics. - Van Cuong Pham, Cuong C. Nguyen, Trung Le, Dinh Phung, Gustavo Carneiro, Thanh-Toan Do:
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning. - Qizhang Feng, Zhimeng Stephen Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, Xia Hu:
Fair Graph Distillation. - Lasse Vuursteen, Botond Szabó, Aad van der Vaart, Harry van Zanten:
Optimal testing using combined test statistics across independent studies. - Xiang Ji, Gen Li:
Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time. - Jimmy T. H. Smith, Shalini De Mello, Jan Kautz, Scott W. Linderman, Wonmin Byeon:
Convolutional State Space Models for Long-Range Spatiotemporal Modeling. - Jiwen Yu, Xuanyu Zhang, Youmin Xu, Jian Zhang:
CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography. - Melissa Dell, Jacob Carlson, Tom Bryan, Emily Silcock, Abhishek Arora, Zejiang Shen, Luca D'Amico-Wong, Quan Le, Pablo Querubin, Leander Heldring:
American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers.
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