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34th NeurIPS 2021
- Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan:
Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. 2021 - Christoph Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert:
Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning. 1-12 - Ahmed Touati, Yann Ollivier:
Learning One Representation to Optimize All Rewards. 13-23 - Nick Whiteley, Annie Gray, Patrick Rubin-Delanchy:
Matrix factorisation and the interpretation of geodesic distance. 24-38 - Jiuxiang Gu, Jason Kuen, Vlad I. Morariu, Handong Zhao, Rajiv Jain, Nikolaos Barmpalios, Ani Nenkova, Tong Sun:
UniDoc: Unified Pretraining Framework for Document Understanding. 39-50 - Liangbin Xie, Xintao Wang, Chao Dong, Zhongang Qi, Ying Shan:
Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution. 51-61 - Dylan Slack, Anna Hilgard, Himabindu Lakkaraju, Sameer Singh:
Counterfactual Explanations Can Be Manipulated. 62-75 - Hengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, Philip S. Yu:
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks. 76-89 - Zhao Tang Luo, Huiyan Sang, Bani K. Mallick:
BAST: Bayesian Additive Regression Spanning Trees for Complex Constrained Domain. 90-102 - Mina Ghadimi Atigh, Martin Keller-Ressel, Pascal Mettes:
Hyperbolic Busemann Learning with Ideal Prototypes. 103-115 - Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler:
Backward-Compatible Prediction Updates: A Probabilistic Approach. 116-128 - Benjamin Kurt Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger:
Truncated Marginal Neural Ratio Estimation. 129-143 - Yiyou Sun, Chuan Guo, Yixuan Li:
ReAct: Out-of-distribution Detection With Rectified Activations. 144-157 - Jogendra Nath Kundu, Siddharth Seth, Anirudh Jamkhandi, Pradyumna YM, Varun Jampani, Anirban Chakraborty, Venkatesh Babu R.:
Non-local Latent Relation Distillation for Self-Adaptive 3D Human Pose Estimation. 158-171 - Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzstein:
Fast Training of Neural Lumigraph Representations using Meta Learning. 172-186 - Stefano Sarao Mannelli, Pierfrancesco Urbani:
Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems. 187-199 - Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, S. M. Ali Eslami, Oriol Vinyals, Felix Hill:
Multimodal Few-Shot Learning with Frozen Language Models. 200-212 - Juha Harviainen, Antti Röyskö
, Mikko Koivisto:
Approximating the Permanent with Deep Rejection Sampling. 213-224 - Yamini Bansal, Preetum Nakkiran, Boaz Barak:
Revisiting Model Stitching to Compare Neural Representations. 225-236 - Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, Zhangyang Wang:
AugMax: Adversarial Composition of Random Augmentations for Robust Training. 237-250 - Andrew Szot, Alexander Clegg, Eric Undersander, Erik Wijmans, Yili Zhao, John M. Turner, Noah Maestre, Mustafa Mukadam, Devendra Singh Chaplot, Oleksandr Maksymets, Aaron Gokaslan, Vladimir Vondrus, Sameer Dharur, Franziska Meier, Wojciech Galuba, Angel X. Chang, Zsolt Kira, Vladlen Koltun, Jitendra Malik, Manolis Savva, Dhruv Batra:
Habitat 2.0: Training Home Assistants to Rearrange their Habitat. 251-266 - Seohong Park, Jaekyeom Kim, Gunhee Kim:
Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods. 267-279 - Jonas Rothfuss, Dominique Heyn, Jinfan Chen, Andreas Krause:
Meta-Learning Reliable Priors in the Function Space. 280-293 - Sang-Hoon Lee, Ji-Hoon Kim, Hyunseung Chung, Seong-Whan Lee:
VoiceMixer: Adversarial Voice Style Mixup. 294-308 - Jason D. Lee, Qi Lei, Nikunj Saunshi, Jiacheng Zhuo:
Predicting What You Already Know Helps: Provable Self-Supervised Learning. 309-323 - Guy Kornowski, Ohad Shamir:
Oracle Complexity in Nonsmooth Nonconvex Optimization. 324-334 - Tao Sheng, Jie Chen, Zhouhui Lian:
CentripetalText: An Efficient Text Instance Representation for Scene Text Detection. 335-346 - Ping Zhang, Rishabh K. Iyer, Ashish Tendulkar, Gaurav Aggarwal, Abir De:
Learning to Select Exogenous Events for Marked Temporal Point Process. 347-361 - Shay Vargaftik, Ran Ben-Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher:
DRIVE: One-bit Distributed Mean Estimation. 362-377 - Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian:
Learning Space Partitions for Path Planning. 378-391 - Chen Gao, Yinfeng Li, Quanming Yao, Depeng Jin, Yong Li:
Progressive Feature Interaction Search for Deep Sparse Network. 392-403 - Yi-Lin Tuan, Connor Pryor, Wenhu Chen, Lise Getoor, William Yang Wang:
Local Explanation of Dialogue Response Generation. 404-416 - Arno Solin, Ella Tamir, Prakhar Verma:
Scalable Inference in SDEs by Direct Matching of the Fokker-Planck-Kolmogorov Equation. 417-429 - Robert Ganian, Viktoriia Korchemna:
The Complexity of Bayesian Network Learning: Revisiting the Superstructure. 430-442 - Kazu Ghalamkari, Mahito Sugiyama:
Fast Tucker Rank Reduction for Non-Negative Tensors Using Mean-Field Approximation. 443-454 - Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj:
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. 455-467 - David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels:
Numerical influence of ReLU'(0) on backpropagation. 468-479 - Jyoti Aneja, Alexander G. Schwing, Jan Kautz, Arash Vahdat:
A Contrastive Learning Approach for Training Variational Autoencoder Priors. 480-493 - Andreas Loukas, Marinos Poiitis, Stefanie Jegelka:
What training reveals about neural network complexity. 494-508 - Zhongzheng Ren, Xiaoming Zhao, Alexander G. Schwing:
Class-agnostic Reconstruction of Dynamic Objects from Videos. 509-522 - Dian Jin, Xin Bing, Yuqian Zhang:
Unique sparse decomposition of low rank matrices. 523-535 - Yonghyeon Lee, Hyeokjun Kwon, Frank C. Park:
Neighborhood Reconstructing Autoencoders. 536-546 - Zhibin Duan, Yishi Xu, Bo Chen, Dongsheng Wang, Chaojie Wang, Mingyuan Zhou:
TopicNet: Semantic Graph-Guided Topic Discovery. 547-559 - Chengshuai Shi, Haifeng Xu, Wei Xiong, Cong Shen:
(Almost) Free Incentivized Exploration from Decentralized Learning Agents. 560-571 - Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, Christopher Ré:
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers. 572-585 - Zifeng Wang, Tong Jian, Aria Masoomi, Stratis Ioannidis, Jennifer G. Dy:
Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness. 586-597 - Changwoo J. Lee, Zhao Tang Luo, Huiyan Sang:
T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs. 598-609 - Rohan R. Paleja, Muyleng Ghuy, Nadun Ranawaka Arachchige, Reed Jensen, Matthew C. Gombolay:
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming. 610-623 - Konrad Czechowski, Tomasz Odrzygózdz, Marek Zbysinski, Michal Zawalski, Krzysztof Olejnik, Yuhuai Wu, Lukasz Kucinski, Piotr Milos:
Subgoal Search For Complex Reasoning Tasks. 624-638 - Tomas Geffner, Justin Domke:
MCMC Variational Inference via Uncorrected Hamiltonian Annealing. 639-651 - Keji He, Yan Huang, Qi Wu, Jianhua Yang, Dong An, Shuanglin Sima, Liang Wang:
Landmark-RxR: Solving Vision-and-Language Navigation with Fine-Grained Alignment Supervision. 652-663 - James Diffenderfer, Brian R. Bartoldson, Shreya Chaganti, Jize Zhang, Bhavya Kailkhura:
A Winning Hand: Compressing Deep Networks Can Improve Out-of-Distribution Robustness. 664-676 - Rui Huang, Andrew Geng, Yixuan Li:
On the Importance of Gradients for Detecting Distributional Shifts in the Wild. 677-689 - Terrance Liu, Giuseppe Vietri, Steven Wu
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods. 690-702 - Clement Gehring, Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling:
Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization. 703-714 - Qijia Jiang:
Mirror Langevin Monte Carlo: the Case Under Isoperimetry. 715-725 - Zhongdao Wang, Hengshuang Zhao, Ya-Li Li, Shengjin Wang, Philip H. S. Torr, Luca Bertinetto:
Do Different Tracking Tasks Require Different Appearance Models? 726-738 - Shahd Safarani, Arne Nix, Konstantin Willeke, Santiago A. Cadena, Kelli Restivo, George H. Denfield, Andreas S. Tolias, Fabian H. Sinz:
Towards robust vision by multi-task learning on monkey visual cortex. 739-751 - Ryan R. Strauss, Junier B. Oliva:
Arbitrary Conditional Distributions with Energy. 752-763 - Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba:
Learning Domain Invariant Representations in Goal-conditioned Block MDPs. 764-776 - Scott Sussex, Caroline Uhler, Andreas Krause:
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. 777-788 - Wasim Huleihel, Arya Mazumdar, Soumyabrata Pal:
Fuzzy Clustering with Similarity Queries. 789-801 - Pascal Notin, José Miguel Hernández-Lobato, Yarin Gal:
Improving black-box optimization in VAE latent space using decoder uncertainty. 802-814 - Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh:
Sample Selection for Fair and Robust Training. 815-827 - Khaled Nakhleh, Santosh Ganji, Ping-Chun Hsieh, I-Hong Hou, Srinivas Shakkottai:
NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RL. 828-839 - Jungwuk Park, Dong-Jun Han, Minseok Choi, Jaekyun Moon:
Sageflow: Robust Federated Learning against Both Stragglers and Adversaries. 840-851 - Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, Timo Aila:
Alias-Free Generative Adversarial Networks. 852-863 - Kwanyoung Kim, Jong Chul Ye:
Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean Images. 864-874 - Yihan Du, Siwei Wang, Zhixuan Fang, Longbo Huang:
Continuous Mean-Covariance Bandits. 875-886 - Mingyu Ding, Zhenfang Chen, Tao Du, Ping Luo, Josh Tenenbaum, Chuang Gan:
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language. 887-899 - Ruizhe Qin, Mengying Li, Hu Ding:
Solving Soft Clustering Ensemble via $k$-Sparse Discrete Wasserstein Barycenter. 900-913 - Aurick Zhou, Sergey Levine:
Bayesian Adaptation for Covariate Shift. 914-927 - Miguel Lázaro-Gredilla, Antoine Dedieu, Dileep George:
Perturb-and-max-product: Sampling and learning in discrete energy-based models. 928-940 - Xiangyu Liu, Hangtian Jia, Ying Wen, Yujing Hu, Yingfeng Chen, Changjie Fan, Zhipeng Hu, Yaodong Yang:
Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games. 941-952 - Sungyoon Lee, Woojin Lee, Jinseong Park, Jaewook Lee:
Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples. 953-964 - Jonathan D. Chang, Masatoshi Uehara, Dhruv Sreenivas, Rahul Kidambi, Wen Sun:
Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial Coverage. 965-979 - Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou:
Global Filter Networks for Image Classification. 980-993 - Xiao Jin, Pin-Yu Chen, Chia-Yi Hsu, Chia-Mu Yu, Tianyi Chen:
Catastrophic Data Leakage in Vertical Federated Learning. 994-1006 - Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Wei Jing, Cheston Tan, Bryan Kian Hsiang Low:
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee. 1007-1021 - Rabeeh Karimi Mahabadi, James Henderson, Sebastian Ruder:
Compacter: Efficient Low-Rank Hypercomplex Adapter Layers. 1022-1035 - Shuxuan Guo, Jose M. Alvarez, Mathieu Salzmann:
Distilling Image Classifiers in Object Detectors. 1036-1047 - Jiaqi Ma, Junwei Deng, Qiaozhu Mei:
Subgroup Generalization and Fairness of Graph Neural Networks. 1048-1061 - Amir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin:
Scaling Neural Tangent Kernels via Sketching and Random Features. 1062-1073 - Haoping Bai, Meng Cao, Ping Huang, Jiulong Shan:
BatchQuant: Quantized-for-all Architecture Search with Robust Quantizer. 1074-1085 - Mingze Xu, Yuanjun Xiong, Hao Chen, Xinyu Li, Wei Xia, Zhuowen Tu, Stefano Soatto:
Long Short-Term Transformer for Online Action Detection. 1086-1099 - Aldo Pacchiano, Jonathan N. Lee, Peter L. Bartlett, Ofir Nachum:
Near Optimal Policy Optimization via REPS. 1100-1110 - Gregory Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado Philip van Hasselt, David Silver:
Self-Consistent Models and Values. 1111-1125 - Takanori Maehara, Hoang NT:
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters. 1126-1141 - Marc Rigter, Bruno Lacerda, Nick Hawes:
Risk-Averse Bayes-Adaptive Reinforcement Learning. 1142-1154 - Yichen Qin, Linhan Yu, Yang Li:
Iterative Connecting Probability Estimation for Networks. 1155-1166 - Yunan Liu, Shanshan Zhang, Yang Li, Jian Yang:
Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation. 1167-1178 - Koby Bibas, Meir Feder, Tal Hassner:
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection. 1179-1191 - Lei Ke, Xia Li, Martin Danelljan, Yu-Wing Tai, Chi-Keung Tang, Fisher Yu:
Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation. 1192-1203 - Amit Attia, Tomer Koren:
Algorithmic Instabilities of Accelerated Gradient Descent. 1204-1214 - Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi:
Learning Optimal Predictive Checklists. 1215-1229 - Sheng Zhang, Zhe Zhang, Siva Theja Maguluri:
Finite Sample Analysis of Average-Reward TD Learning and $Q$-Learning. 1230-1242 - Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza:
Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic. 1243-1255 - Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. 1256-1272 - Michael Janner, Qiyang Li, Sergey Levine:
Offline Reinforcement Learning as One Big Sequence Modeling Problem. 1273-1286 - Kate Donahue, Jon M. Kleinberg:
Optimality and Stability in Federated Learning: A Game-theoretic Approach. 1287-1298 - Rong Ge, Yunwei Ren, Xiang Wang, Mo Zhou:
Understanding Deflation Process in Over-parametrized Tensor Decomposition. 1299-1311 - Vikrant Singhal, Thomas Steinke:
Privately Learning Subspaces. 1312-1324 - Nived Rajaraman, Yanjun Han, Lin Yang
On the Value of Interaction and Function Approximation in Imitation Learning. 1325-1336 - Aliakbar Panahi, Seyran Saeedi, Tom Arodz:
Shapeshifter: a Parameter-efficient Transformer using Factorized Reshaped Matrices. 1337-1350 - Masahiro Kato, Kenichiro McAlinn, Shota Yasui:
The Adaptive Doubly Robust Estimator and a Paradox Concerning Logging Policy. 1351-1364 - Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson:
Regularized Softmax Deep Multi-Agent Q-Learning. 1365-1377 - Niv Giladi, Zvika Ben-Haim, Sella Nevo, Yossi Matias, Daniel Soudry:
Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling. 1378-1389 - Leon Bergen, Timothy J. O'Donnell, Dzmitry Bahdanau:
Systematic Generalization with Edge Transformers. 1390-1402 - Aljaz Bozic, Pablo R. Palafox, Justus Thies, Angela Dai, Matthias Nießner:
TransformerFusion: Monocular RGB Scene Reconstruction using Transformers. 1403-1414 - Yang Song, Conor Durkan, Iain Murray, Stefano Ermon:
Maximum Likelihood Training of Score-Based Diffusion Models. 1415-1428 - Tian Ye, Simon S. Du:
Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization. 1429-1439 - Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding
Adaptive Data Augmentation on Temporal Graphs. 1440-1452 - D. Khuê Lê-Huu, Karteek Alahari:
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond. 1453-1467 - Taebum Kim, Eunji Jeong, Geon-Woo Kim, Yunmo Koo, Sehoon Kim, Gyeong-In Yu, Byung-Gon Chun:
Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs. 1468-1480 - Sébastien M. R. Arnold, Guneet S. Dhillon, Avinash Ravichandran, Stefano Soatto:
Uniform Sampling over Episode Difficulty. 1481-1493 - Burak Varici, Karthikeyan Shanmugam
Scalable Intervention Target Estimation in Linear Models. 1494-1505 - Allen Nie, Emma Brunskill, Chris Piech:
Play to Grade: Testing Coding Games as Classifying Markov Decision Process. 1506-1518 - Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu:
Distributional Reinforcement Learning for Multi-Dimensional Reward Functions. 1519-1529 - Ofir Lindenbaum, Uri Shaham, Erez Peterfreund, Jonathan Svirsky, Nicolas Casey, Yuval Kluger:
Differentiable Unsupervised Feature Selection based on a Gated Laplacian. 1530-1542 - Clarice Poon, Gabriel Peyré:
Smooth Bilevel Programming for Sparse Regularization. 1543-1555 - Frances Ding, Jean-Stanislas Denain, Jacob Steinhardt:
Grounding Representation Similarity Through Statistical Testing. 1556-1568 - Mingde Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio:
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning. 1569-1581 - Weitong Zhang, Dongruo Zhou, Quanquan Gu:
Reward-Free Model-Based Reinforcement Learning with Linear Function Approximation. 1582-1593 - Ben Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein:
Beltrami Flow and Neural Diffusion on Graphs. 1594-1609 - Gonzalo Jaimovitch-López, David Castellano Falcón, César Ferri, José Hernández-Orallo:
Think Big, Teach Small: Do Language Models Distil Occam's Razor? 1610-1623 - Hermanni Hälvä, Sylvain Le Corff, Luc Lehéricy, Jonathan So, Yongjie Zhu, Elisabeth Gassiat, Aapo Hyvärinen:
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA. 1624-1633 - Jiayang Xu, Aniruddhe Pradhan, Karthik Duraisamy:
Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical Systems. 1634-1645 - Guangmo Tong:
USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems. 1646-1659 - Isaac Gibbs, Emmanuel J. Candès:
Adaptive Conformal Inference Under Distribution Shift. 1660-1672 - Lassi Meronen, Martin Trapp, Arno Solin:
Periodic Activation Functions Induce Stationarity. 1673-1685 - David Acuna, Jonah Philion, Sanja Fidler:
Towards Optimal Strategies for Training Self-Driving Perception Models in Simulation. 1686-1699 - Yu Hao, Xin Cao, Yufan Sheng, Yixiang Fang, Wei Wang:
KS-GNN: Keywords Search over Incomplete Graphs via Graphs Neural Network. 1700-1712 - Leonardo Cotta, Christopher Morris, Bruno Ribeiro:
Reconstruction for Powerful Graph Representations. 1713-1726 - Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays:
Revealing and Protecting Labels in Distributed Training. 1727-1738 - Victor-Alexandru Darvariu, Stephen Hailes, Mirco Musolesi:
Solving Graph-based Public Goods Games with Tree Search and Imitation Learning. 1739-1751 - Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang:
Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence. 1752-1765 - Qi Zhu, Carl Yang, Yidan Xu, Haonan Wang, Chao Zhang, Jiawei Han:
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization. 1766-1779 - Xuxi Chen, Tianlong Chen, Zhenyu Zhang, Zhangyang Wang:
You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership. 1780-1791 - Haochuan Li, Yi Tian, Jingzhao Zhang, Ali Jadbabaie:
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization. 1792-1804 - Ziwei Ji, Justin D. Li, Matus Telgarsky:
Early-stopped neural networks are consistent. 1805-1817 - Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu:
NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM. 1818-1830 - Roshni Sahoo, Shengjia Zhao, Alyssa Chen, Stefano Ermon:
Reliable Decisions with Threshold Calibration. 1831-1844 - Salva Rühling Cachay, Benedikt Boecking, Artur Dubrawski:
End-to-End Weak Supervision. 1845-1857 - Vasu Singla, Songwei Ge, Ronen Basri, David W. Jacobs:
Shift Invariance Can Reduce Adversarial Robustness. 1858-1871 - Grant Schoenebeck, Biaoshuai Tao:
Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences. 1872-1883 - Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel:
Replay-Guided Adversarial Environment Design. 1884-1897 - Nathan Grinsztajn, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist:
There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning. 1898-1911 - Ingmar Schubert, Danny Driess, Ozgur S. Oguz, Marc Toussaint:
Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics. 1912-1924 - Jinhee Lee, Haeri Kim, Youngkyu Hong, Hye Won Chung:
Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks. 1925-1938 - Maria Dimakopoulou, Zhimei Ren, Zhengyuan Zhou:
Online Multi-Armed Bandits with Adaptive Inference. 1939-1951 - Constantinos Daskalakis, Patroklos Stefanou, Rui Yao, Emmanouil Zampetakis
Efficient Truncated Linear Regression with Unknown Noise Variance. 1952-1963 - Lingke Kong, Chenyu Lian, Detian Huang, Zhenjiang Li, Yanle Hu, Qichao Zhou:
Breaking the Dilemma of Medical Image-to-image Translation. 1964-1978 - Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Doina Precup:
Temporally Abstract Partial Models. 1979-1991 - Shengcai Liao, Ling Shao:
TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification. 1992-2003 - Harsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche:
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs. 2004-2017 - Alexander Miserlis Hoyle, Pranav Goel, Andrew Hian-Cheong, Denis Peskov, Jordan L. Boyd-Graber, Philip Resnik:
Is Automated Topic Model Evaluation Broken? The Incoherence of Coherence. 2018-2033 - Shuwen Liu, Bernardo Cuenca Grau, Ian Horrocks, Egor V. Kostylev:
INDIGO: GNN-Based Inductive Knowledge Graph Completion Using Pair-Wise Encoding. 2034-2045 - Harshay Shah, Prateek Jain, Praneeth Netrapalli:
Do Input Gradients Highlight Discriminative Features? 2046-2059 - Shai Feldman, Stephen Bates, Yaniv Romano:
Improving Conditional Coverage via Orthogonal Quantile Regression. 2060-2071 - Liwang Zhu, Qi Bao, Zhongzhi Zhang:
Minimizing Polarization and Disagreement in Social Networks via Link Recommendation. 2072-2084 - Shasha Li, Abhishek Aich, Shitong Zhu, M. Salman Asif, Chengyu Song, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy:
Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric Transformations. 2085-2096 - Uri Sherman, Tomer Koren, Yishay Mansour:
Optimal Rates for Random Order Online Optimization. 2097-2108 - Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio:
Discrete-Valued Neural Communication. 2109-2121 - Yifan Chen, Qi Zeng, Heng Ji, Yun Yang:
Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method. 2122-2135 - Zhuchen Shao, Hao Bian, Yang Chen, Yifeng Wang, Jian Zhang, Xiangyang Ji, Yongbing Zhang:
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification. 2136-2147 - Erlin Pan, Zhao Kang:
Multi-view Contrastive Graph Clustering. 2148-2159 - Xintian Han, Mark Goldstein, Aahlad Manas Puli, Thomas Wies, Adler J. Perotte, Rajesh Ranganath:
Inverse-Weighted Survival Games. 2160-2172 - Alec Farid, Anirudha Majumdar:
Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability. 2173-2186 - Samuel Daulton, Maximilian Balandat, Eytan Bakshy:
Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement. 2187-2200 - Jagdeep Singh Bhatia, Holly Jackson, Yunsheng Tian, Jie Xu, Wojciech Matusik:
Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robots. 2201-2214 - Yoav Wald, Amir Feder, Daniel Greenfeld, Uri Shalit:
On Calibration and Out-of-Domain Generalization. 2215-2227 - Junyu Zhang, Chengzhuo Ni, Zheng Yu, Csaba Szepesvári, Mengdi Wang:
On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method. 2228-2240 - Zahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg:
Circa: Stochastic ReLUs for Private Deep Learning. 2241-2252 - Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Reinforcement Learning in Reward-Mixing MDPs. 2253-2264 - Mark Herbster, Stephen Pasteris, Fabio Vitale, Massimiliano Pontil:
A Gang of Adversarial Bandits. 2265-2279 - Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl:
Explaining Hyperparameter Optimization via Partial Dependence Plots. 2280-2291 - Fengzhuo Zhang, Vincent Y. F. Tan:
Robustifying Algorithms of Learning Latent Trees with Vector Variables. 2292-2302 - Zheng Zhan, Liang Zhao:
Representation Learning on Spatial Networks. 2303-2318 - Xuhui Fan, Bin Li, Feng Zhou, Scott A. Sisson:
Continuous-time edge modelling using non-parametric point processes. 2319-2330 - Feng Zhu, Andrew R. Sedler, Harrison A. Grier, Nauman Ahad, Mark A. Davenport, Matthew T. Kaufman, Andrea Giovannucci, Chethan Pandarinath:
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time. 2331-2345 - Ji Lin, Wei-Ming Chen, Han Cai, Chuang Gan, Song Han:
Memory-efficient Patch-based Inference for Tiny Deep Learning. 2346-2358 - Yipei Wang, Xiaoqian Wang:
Self-Interpretable Model with Transformation Equivariant Interpretation. 2359-2372 - Emmanouil V. Vlatakis-Gkaragkounis
Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent. 2373-2386 - Constantin Philippenko, Aymeric Dieuleveut:
Preserved central model for faster bidirectional compression in distributed settings. 2387-2399 - Zhifeng Kong, Kamalika Chaudhuri:
Understanding Instance-based Interpretability of Variational Auto-Encoders. 2400-2412 - Feng Liu, Xiaoming Liu:
Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image. 2413-2426 - Yusuke Iwasawa, Yutaka Matsuo:
Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization. 2427-2440 - Xuezhe Ma, Xiang Kong, Sinong Wang, Chunting Zhou, Jonathan May, Hao Ma, Luke Zettlemoyer:
Luna: Linear Unified Nested Attention. 2441-2453 - Raanan Y. Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik:
Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias. 2454-2465 - Charles Packer, Pieter Abbeel, Joseph E. Gonzalez:
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL. 2466-2477 - Kai Xu, Akash Srivastava, Dan Gutfreund, Felix Sosa, Tomer D. Ullman, Josh Tenenbaum, Charles Sutton:
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics. 2478-2490 - Zongxin Yang, Yunchao Wei, Yi Yang:
Associating Objects with Transformers for Video Object Segmentation. 2491-2502 - Nima Dehmamy, Robin Walters, Yanchen Liu, Dashun Wang, Rose Yu:
Automatic Symmetry Discovery with Lie Algebra Convolutional Network. 2503-2515 - Maciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski:
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. 2516-2528 - Tai-Yu Pan, Cheng Zhang, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, Wei-Lun Chao:
On Model Calibration for Long-Tailed Object Detection and Instance Segmentation. 2529-2542 - Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu:
ReSSL: Relational Self-Supervised Learning with Weak Augmentation. 2543-2555 - Manel Baradad Jurjo, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba:
Learning to See by Looking at Noise. 2556-2569 - Maksim Velikanov, Dmitry Yarotsky:
Explicit loss asymptotics in the gradient descent training of neural networks. 2570-2582 - Yizhuo Li, Miao Hao, Zonglin Di, Nitesh B. Gundavarapu, Xiaolong Wang:
Test-Time Personalization with a Transformer for Human Pose Estimation. 2583-2597 - Zhenyu Xie, Zaiyu Huang, Fuwei Zhao, Haoye Dong, Michael Kampffmeyer, Xiaodan Liang:
Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN. 2598-2610 - Hannah Rose Kirk
Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models. 2611-2624 - Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Liò, Guido F. Montúfar, Michael M. Bronstein:
Weisfeiler and Lehman Go Cellular: CW Networks. 2625-2640 - Tiantian He, Yew Soon Ong, Lu Bai:
Learning Conjoint Attentions for Graph Neural Nets. 2641-2653 - Shinji Ito:
Hybrid Regret Bounds for Combinatorial Semi-Bandits and Adversarial Linear Bandits. 2654-2667 - Hongyu Gong, Yun Tang, Juan Miguel Pino, Xian Li:
Pay Better Attention to Attention: Head Selection in Multilingual and Multi-Domain Sequence Modeling. 2668-2681 - Tsuyoshi Idé, Georgios Kollias, Dzung T. Phan, Naoki Abe:
Cardinality-Regularized Hawkes-Granger Model. 2682-2694 - Yulun Zhang, Huan Wang, Can Qin, Yun Fu:
Aligned Structured Sparsity Learning for Efficient Image Super-Resolution. 2695-2706 - Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong:
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks. 2707-2720 - Shengjie Wang, Tianyi Zhou, Chandrashekhar Lavania, Jeff A. Bilmes:
Constrained Robust Submodular Partitioning. 2721-2732 - Sungjin Im, Ravi Kumar, Mahshid Montazer Qaem, Manish Purohit:
Online Knapsack with Frequency Predictions. 2733-2743 - Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus:
On Component Interactions in Two-Stage Recommender Systems. 2744-2757 - Minsu Kim, Joanna Hong, Yong Man Ro:
Lip to Speech Synthesis with Visual Context Attentional GAN. 2758-2770 - Jikai Jin, Bohang Zhang, Haiyang Wang, Liwei Wang:
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis. 2771-2782 - Kibeom Kim, Min Whoo Lee, Yoonsung Kim, Je-Hwan Ryu, Min Su Lee, Byoung-Tak Zhang:
Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning. 2783-2795 - Jonas Köhler, Andreas Krämer, Frank Noé:
Smooth Normalizing Flows. 2796-2809 - Shaofei Wang, Marko Mihajlovic, Qianli Ma, Andreas Geiger, Siyu Tang
MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images. 2810-2822 - Foivos Alimisis, Peter Davies, Bart Vandereycken, Dan Alistarh:
Distributed Principal Component Analysis with Limited Communication. 2823-2834 - Michal Derezinski, Jonathan Lacotte, Mert Pilanci, Michael W. Mahoney:
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update. 2835-2847 - Jiahua Dong, Zhen Fang, Anjin Liu, Gan Sun, Tongliang Liu:
Confident Anchor-Induced Multi-Source Free Domain Adaptation. 2848-2860 - Benyou Wang, Emanuele Di Buccio, Massimo Melucci:
Word2Fun: Modelling Words as Functions for Diachronic Word Representation. 2861-2872 - Christian Kümmerle, Claudio Mayrink Verdun, Dominik Stöger:
Iteratively Reweighted Least Squares for Basis Pursuit with Global Linear Convergence Rate. 2873-2886 - Justin T. Chiu, Yuntian Deng, Alexander M. Rush:
Low-Rank Constraints for Fast Inference in Structured Models. 2887-2898 - Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu:
Accumulative Poisoning Attacks on Real-time Data. 2899-2912 - Sanae Amani, Christos Thrampoulidis:
UCB-based Algorithms for Multinomial Logistic Regression Bandits. 2913-2924 - Keith Battocchi, Eleanor Dillon, Maggie Hei, Greg Lewis, Miruna Oprescu, Vasilis Syrgkanis:
Estimating the Long-Term Effects of Novel Treatments. 2925-2935 - Chaoqun Wang, Shaobo Min, Xuejin Chen, Xiaoyan Sun, Houqiang Li:
Dual Progressive Prototype Network for Generalized Zero-Shot Learning. 2936-2948 - Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar:
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity. 2949-2964 - Yunhui Long, Boxin Wang, Zhuolin Yang, Bhavya Kailkhura, Aston Zhang, Carl A. Gunter, Bo Li:
G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators. 2965-2977 - Pranjal Awasthi, Natalie Frank, Mehryar Mohri:
On the Existence of The Adversarial Bayes Classifier. 2978-2990 - Denizalp Goktas, Amy Greenwald:
Convex-Concave Min-Max Stackelberg Games. 2991-3003 - Ilija Bogunovic, Andreas Krause:
Misspecified Gaussian Process Bandit Optimization. 3004-3015 - Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn:
Visual Adversarial Imitation Learning using Variational Models. 3016-3028 - Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu:
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning. 3029-3042 - Chunjong Park, Anas Awadalla, Tadayoshi Kohno, Shwetak N. Patel:
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection. 3043-3056 - Nataly Brukhim, Elad Hazan, Shay Moran, Indraneel Mukherjee, Robert E. Schapire:
Multiclass Boosting and the Cost of Weak Learning. 3057-3067 - Calvin Tsay, Jan Kronqvist, Alexander Thebelt, Ruth Misener:
Partition-Based Formulations for Mixed-Integer Optimization of Trained ReLU Neural Networks. 3068-3080 - A. Feder Cooper, Yucheng Lu, Jessica Forde, Christopher De Sa:
Hyperparameter Optimization Is Deceiving Us, and How to Stop It. 3081-3095 - Alireza Fallah, Kristian Georgiev, Aryan Mokhtari, Asuman E. Ozdaglar:
On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning. 3096-3107 - Chaoyue Song, Jiacheng Wei, Ruibo Li, Fayao Liu, Guosheng Lin:
3D Pose Transfer with Correspondence Learning and Mesh Refinement. 3108-3120 - Adeline Fermanian, Pierre Marion, Jean-Philippe Vert, Gérard Biau:
Framing RNN as a kernel method: A neural ODE approach. 3121-3134 - Jianbo Ouyang, Hui Wu, Min Wang, Wengang Zhou, Houqiang Li:
Contextual Similarity Aggregation with Self-attention for Visual Re-ranking. 3135-3148 - Praveen Venkatesh, Sanghamitra Dutta, Neil Mehta, Pulkit Grover:
Can Information Flows Suggest Targets for Interventions in Neural Circuits? 3149-3162 - Mingchen Li, Xuechen Zhang, Christos Thrampoulidis, Jiasi Chen, Samet Oymak:
AutoBalance: Optimized Loss Functions for Imbalanced Data. 3163-3177 - Zhaozhi Qian, Yao Zhang, Ioana Bica, Angela M. Wood, Mihaela van der Schaar:
SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes. 3178-3190 - Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas, Alistair Stewart:
Statistical Query Lower Bounds for List-Decodable Linear Regression. 3191-3204 - Ziwei Xu, Xudong Shen, Yongkang Wong, Mohan S. Kankanhalli:
Unsupervised Motion Representation Learning with Capsule Autoencoders. 3205-3217 - Yizhou Zhang, Karishma Sharma, Yan Liu:
VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media. 3218-3231 - Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin:
An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders. 3232-3243 - Yuan Liang, Weikun Han, Liang Qiu, Chen Wu, Yiting Shao, Kun Wang, Lei He:
Exploring Forensic Dental Identification with Deep Learning. 3244-3258 - Yuanhao Cai, Xiaowan Hu, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Donglai Wei:
Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training. 3259-3270 - Jianhong Wang, Wangkun Xu, Yunjie Gu, Wenbin Song, Tim C. Green:
Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks. 3271-3284 - Feihu Zhang, Philip H. S. Torr, René Ranftl, Stephan R. Richter:
Looking Beyond Single Images for Contrastive Semantic Segmentation Learning. 3285-3297 - Tom Hess, Michal Moshkovitz, Sivan Sabato:
A Constant Approximation Algorithm for Sequential Random-Order No-Substitution k-Median Clustering. 3298-3308 - Pavel Izmailov, Patrick Nicholson, Sanae Lotfi, Andrew Gordon Wilson:
Dangers of Bayesian Model Averaging under Covariate Shift. 3309-3322 - Meena Jagadeesan, Alexander Wei, Yixin Wang, Michael I. Jordan, Jacob Steinhardt:
Learning Equilibria in Matching Markets from Bandit Feedback. 3323-3335 - Christoph Hertrich, Amitabh Basu, Marco Di Summa, Martin Skutella:
Towards Lower Bounds on the Depth of ReLU Neural Networks. 3336-3348 - Geoff Pleiss, John P. Cunningham:
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective. 3349-3363 - Jacob A. Zavatone-Veth, Cengiz Pehlevan:
Exact marginal prior distributions of finite Bayesian neural networks. 3364-3375 - Zichen Miao, Ze Wang, Xiuyuan Cheng, Qiang Qiu:
Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks. 3376-3388 - Navid Naderializadeh, Joseph F. Comer, Reed W. Andrews, Heiko Hoffmann, Soheil Kolouri:
Pooling by Sliced-Wasserstein Embedding. 3389-3400 - Niladri S. Chatterji, Aldo Pacchiano, Peter L. Bartlett, Michael I. Jordan:
On the Theory of Reinforcement Learning with Once-per-Episode Feedback. 3401-3412 - Kuan-Lin Chen, Ching Hua Lee, Harinath Garudadri, Bhaskar D. Rao:
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees. 3413-3424 - Thomas Berrett, Yi Yu:
Locally private online change point detection. 3425-3437 - Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish:
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. 3438-3450 - Francesco D'Angelo, Vincent Fortuin
Repulsive Deep Ensembles are Bayesian. 3451-3465 - Siu Lun Chau, Jean-Francois Ton, Javier González, Yee Whye Teh, Dino Sejdinovic:
BayesIMP: Uncertainty Quantification for Causal Data Fusion. 3466-3477 - Yaoyao Liu, Bernt Schiele
RMM: Reinforced Memory Management for Class-Incremental Learning. 3478-3490 - Jie Bu, Arka Daw, M. Maruf, Anuj Karpatne:
Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM). 3491-3503 - Xidong Feng, Oliver Slumbers, Ziyu Wan, Bo Liu, Stephen McAleer, Ying Wen, Jun Wang, Yaodong Yang:
Neural Auto-Curricula in Two-Player Zero-Sum Games. 3504-3517 - Patrick Esser, Robin Rombach, Andreas Blattmann, Björn Ommer:
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis. 3518-3532 - Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts:
From global to local MDI variable importances for random forests and when they are Shapley values. 3533-3543 - Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou:
Adversarial Robustness of Streaming Algorithms through Importance Sampling. 3544-3557 - Anji Liu, Guy Van den Broeck:
Tractable Regularization of Probabilistic Circuits. 3558-3570 - Eric Mintun, Alexander Kirillov, Saining Xie:
On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness. 3571-3583 - Ashraful Islam, Chun-Fu (Richard) Chen, Rameswar Panda, Leonid Karlinsky, Rogério Feris, Richard J. Radke:
Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data. 3584-3595 - Guoyuan An, Yuchi Huo, Sung Eui Yoon:
Hypergraph Propagation and Community Selection for Objects Retrieval. 3596-3608 - Taiji Suzuki, Atsushi Nitanda:
Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space. 3609-3621 - Kaan Ozkara, Navjot Singh, Deepesh Data, Suhas N. Diggavi:
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning. 3622-3634 - Jiaxing Huang, Dayan Guan, Aoran Xiao, Shijian Lu:
Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data. 3635-3649 - Peter Hase, Harry Xie, Mohit Bansal:
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations. 3650-3666 - Nikos Vlassis, Ashok Chandrashekar, Fernando Amat Gil, Nathan Kallus:
Control Variates for Slate Off-Policy Evaluation. 3667-3679 - Nicklas Hansen, Hao Su, Xiaolong Wang:
Stabilizing Deep Q-Learning with ConvNets and Vision Transformers under Data Augmentation. 3680-3693 - Hang Lai, Jian Shen, Weinan Zhang, Yimin Huang, Xing Zhang, Ruiming Tang, Yong Yu, Zhenguo Li:
On Effective Scheduling of Model-based Reinforcement Learning. 3694-3705 - Dominic Gonschorek, Larissa Höfling, Klaudia P. Szatko, Katrin Franke, Timm Schubert, Benjamin A. Dunn, Philipp Berens, David A. Klindt, Thomas Euler:
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience. 3706-3719 - Prithviraj Ammanabrolu, Mark O. Riedl:
Learning Knowledge Graph-based World Models of Textual Environments. 3720-3731 - Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong:
Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization. 3732-3743 - Nate Veldt, Austin R. Benson, Jon M. Kleinberg:
Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components. 3744-3756 - Lulu Zheng, Jiarui Chen, Jianhao Wang, Jiamin He, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao, Chongjie Zhang:
Episodic Multi-agent Reinforcement Learning with Curiosity-driven Exploration. 3757-3769 - Amrith Setlur, Oscar Li, Virginia Smith:
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution. 3770-3783 - Zhiquan Wen, Guanghui Xu, Mingkui Tan, Qingyao Wu, Qi Wu:
Debiased Visual Question Answering from Feature and Sample Perspectives. 3784-3796 - Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang:
Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness. 3797-3810 - Mingtian Zhang, Andi Zhang, Steven McDonagh:
On the Out-of-distribution Generalization of Probabilistic Image Modelling. 3811-3823 - Qiujiang Jin, Aryan Mokhtari:
Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach. 3824-3835 - Moshe Eliasof, Eldad Haber, Eran Treister:
PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations. 3836-3849 - David Lindner
Information Directed Reward Learning for Reinforcement Learning. 3850-3862 - Koki Kawabata, Siddharth Bhatia, Rui Liu, Mohit Wadhwa, Bryan Hooi:
SSMF: Shifting Seasonal Matrix Factorization. 3863-3873 - Tommaso Salvatori, Yuhang Song, Yujian Hong, Lei Sha, Simon Frieder, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz:
Associative Memories via Predictive Coding. 3874-3886 - Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh:
Robust and differentially private mean estimation. 3887-3901 - Kenneth Derek, Phillip Isola:
Adaptable Agent Populations via a Generative Model of Policies. 3902-3913 - Linus Hamilton, Ankur Moitra:
A No-go Theorem for Robust Acceleration in the Hyperbolic Plane. 3914-3924 - Ishaq Aden-Ali, Hassan Ashtiani, Christopher Liaw:
Privately Learning Mixtures of Axis-Aligned Gaussians. 3925-3938 - Idan Kligvasser, Tamar Rott Shaham, Yuval Bahat, Tomer Michaeli:
Deep Self-Dissimilarities as Powerful Visual Fingerprints. 3939-3951 - Ioana Bica, Daniel Jarrett, Mihaela van der Schaar:
Invariant Causal Imitation Learning for Generalizable Policies. 3952-3964 - Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan:
CoAtNet: Marrying Convolution and Attention for All Data Sizes. 3965-3977 - Yan Liu, Zhijie Zhang, Li Niu, Junjie Chen, Liqing Zhang:
Mixed Supervised Object Detection by Transferring Mask Prior and Semantic Similarity. 3978-3990 - Chenghao Li, Tonghan Wang, Chengjie Wu, Qianchuan Zhao, Jun Yang, Chongjie Zhang:
Celebrating Diversity in Shared Multi-Agent Reinforcement Learning. 3991-4002 - Liu Leqi, Fatma Kilinç-Karzan, Zachary C. Lipton, Alan L. Montgomery:
Rebounding Bandits for Modeling Satiation Effects. 4003-4014 - Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik:
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond. 4015-4027 - Divyansh Garg, Shuvam Chakraborty, Chris Cundy, Jiaming Song, Stefano Ermon:
IQ-Learn: Inverse soft-Q Learning for Imitation. 4028-4039 - Dongmin Park, Hwanjun Song, Minseok Kim, Jae-Gil Lee:
Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data. 4040-4052 - Janardhan Kulkarni, Yin Tat Lee, Daogao Liu:
Private Non-smooth ERM and SCO in Subquadratic Steps. 4053-4064 - Ming Yin, Yu-Xiang Wang:
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism. 4065-4078 - Robin Ru, Clare Lyle, Lisa Schut, Miroslav Fil, Mark van der Wilk, Yarin Gal:
Speedy Performance Estimation for Neural Architecture Search. 4079-4092 - Andrew Y. K. Foong, Wessel P. Bruinsma, David R. Burt, Richard E. Turner:
How Tight Can PAC-Bayes be in the Small Data Regime? 4093-4105 - Gregory Clark:
Deep Synoptic Monte-Carlo Planning in Reconnaissance Blind Chess. 4106-4119 - Shoutik Mukherjee, Behtash Babadi:
Dynamic Analysis of Higher-Order Coordination in Neuronal Assemblies via De-Sparsified Orthogonal Matching Pursuit. 4120-4133 - Erik Lindgren, Sashank J. Reddi, Ruiqi Guo, Sanjiv Kumar:
Efficient Training of Retrieval Models using Negative Cache. 4134-4146 - Xiuwen Gong, Dong Yuan, Wei Bao:
Understanding Partial Multi-Label Learning via Mutual Information. 4147-4156 - Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust:
Environment Generation for Zero-Shot Compositional Reinforcement Learning. 4157-4169 - Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Optimizing Conditional Value-At-Risk of Black-Box Functions. 4170-4180 - Victor Garcia Satorras, Emiel Hoogeboom, Fabian Fuchs, Ingmar Posner, Max Welling:
E(n) Equivariant Normalizing Flows. 4181-4192 - Chongjian Ge, Youwei Liang, Yibing Song, Jianbo Jiao, Jue Wang, Ping Luo:
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning. 4193-4206 - Severi Rissanen, Pekka Marttinen:
A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models. 4207-4217 - Sven Gowal, Sylvestre-Alvise Rebuffi, Olivia Wiles, Florian Stimberg, Dan Andrei Calian, Timothy A. Mann:
Improving Robustness using Generated Data. 4218-4233 - Lu Yu, Krishnakumar Balasubramanian, Stanislav Volgushev, Murat A. Erdogdu:
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias. 4234-4248 - Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen:
Learning to Learn Graph Topologies. 4249-4262 - Jaehoon Lee, Jihyeon Hyeong, Jinsung Jeon, Noseong Park, Jihoon Cho:
Invertible Tabular GANs: Killing Two Birds with One Stone for Tabular Data Synthesis. 4263-4273 - Chenning Yu, Sicun Gao:
Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks. 4274-4289 - Wenbo Ren, Jia Liu, Ness B. Shroff:
Sample Complexity Bounds for Active Ranking from Multi-wise Comparisons. 4290-4300 - Ming Gao, Bryon Aragam:
Efficient Bayesian network structure learning via local Markov boundary search. 4301-4313 - Byung-Hoon Kim, Jong Chul Ye, Jae-Jin Kim:
Learning Dynamic Graph Representation of Brain Connectome with Spatio-Temporal Attention. 4314-4327 - Sicheng Zhu, Bang An, Furong Huang:
Understanding the Generalization Benefit of Model Invariance from a Data Perspective. 4328-4341 - Zihan Zhang, Jiaqi Yang, Xiangyang Ji, Simon S. Du:
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP. 4342-4355 - Xinshuai Dong, Anh Tuan Luu, Min Lin, Shuicheng Yan, Hanwang Zhang:
How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness? 4356-4369 - Robert Lieck, Martin Rohrmeier:
Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks. 4370-4383 - Peter Richtárik, Igor Sokolov, Ilyas Fatkhullin:
EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback. 4384-4396 - Kamélia Daudel, Randal Douc:
Mixture weights optimisation for Alpha-Divergence Variational Inference. 4397-4408 - Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang:
Instance-dependent Label-noise Learning under a Structural Causal Model. 4409-4420 - Gavin Kerrigan, Padhraic Smyth, Mark Steyvers:
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration. 4421-4434 - Debjit Paria, Abhishek Sinha:
$\texttt{LeadCache}$: Regret-Optimal Caching in Networks. 4435-4447 - Prasad Gabbur, Manjot Bilkhu, Javier R. Movellan:
Probabilistic Attention for Interactive Segmentation. 4448-4460 - Kaiji Lu, Zifan Wang, Piotr Mardziel, Anupam Datta:
Influence Patterns for Explaining Information Flow in BERT. 4461-4474 - Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian:
Robust Regression Revisited: Acceleration and Improved Estimation Rates. 4475-4488 - Yue Zhao, Ryan A. Rossi, Leman Akoglu:
Automatic Unsupervised Outlier Model Selection. 4489-4502 - Daiki Chijiwa, Shin'ya Yamaguchi, Yasutoshi Ida, Kenji Umakoshi, Tomohiro Inoue:
Pruning Randomly Initialized Neural Networks with Iterative Randomization. 4503-4513 - Hongwei Xue, Yupan Huang, Bei Liu, Houwen Peng, Jianlong Fu, Houqiang Li, Jiebo Luo:
Probing Inter-modality: Visual Parsing with Self-Attention for Vision-and-Language Pre-training. 4514-4528 - Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang:
Stability and Generalization of Bilevel Programming in Hyperparameter Optimization. 4529-4541 - Xiang Zhou, Yi Xiong, Ningyuan Chen, Xuefeng Gao:
Regime Switching Bandits. 4542-4554 - Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Jiawei Li, Sung-Ho Bae, Zhenguo Li:
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps. 4555-4569 - Suhas Vijaykumar:
Localization, Convexity, and Star Aggregation. 4570-4581 - Mugalodi Rakesh, Jogendra Nath Kundu, Varun Jampani, Venkatesh Babu R.:
Aligning Silhouette Topology for Self-Adaptive 3D Human Pose Recovery. 4582-4593 - Zhimeng Pan, Zheng Wang, Jeff M. Phillips, Shandian Zhe:
Self-Adaptable Point Processes with Nonparametric Time Decays. 4594-4606 - Ron Dorfman, Idan Shenfeld, Aviv Tamar:
Offline Meta Reinforcement Learning - Identifiability Challenges and Effective Data Collection Strategies. 4607-4618 - Sihyun Yu, Sungsoo Ahn, Le Song, Jinwoo Shin:
RoMA: Robust Model Adaptation for Offline Model-based Optimization. 4619-4631 - Martin Klissarov, Doina Precup:
Flexible Option Learning. 4632-4646 - Dachao Lin, Ruoyu Sun, Zhihua Zhang:
Faster Directional Convergence of Linear Neural Networks under Spherically Symmetric Data. 4647-4660 - Matteo Almanza, Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi, Giuseppe Re:
Online Facility Location with Multiple Advice. 4661-4673 - Alexander Meulemans, Matilde Tristany Farinha, Javier García Ordóñez, Pau Vilimelis Aceituno, João Sacramento, Benjamin F. Grewe:
Credit Assignment in Neural Networks through Deep Feedback Control. 4674-4687 - Silvio Lattanzi, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang, Rudy Zhou:
Robust Online Correlation Clustering. 4688-4698 - Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Benjamin J. Lengerich, Rich Caruana, Geoffrey E. Hinton:
Neural Additive Models: Interpretable Machine Learning with Neural Nets. 4699-4711 - Sai Vemprala, Sami Mian, Ashish Kapoor:
Representation Learning for Event-based Visuomotor Policies. 4712-4724 - Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Kernel Functional Optimisation. 4725-4737 - Alex H. Williams, Erin Kunz, Simon Kornblith, Scott W. Linderman:
Generalized Shape Metrics on Neural Representations. 4738-4750 - Liang Yang, Mengzhe Li, Liyang Liu, Bingxin Niu, Chuan Wang, Xiaochun Cao, Yuanfang Guo:
Diverse Message Passing for Attribute with Heterophily. 4751-4763 - Mete Kemertas, Tristan Aumentado-Armstrong:
Towards Robust Bisimulation Metric Learning. 4764-4777 - Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka:
Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning. 4778-4791 - Ziping Xu, Ambuj Tewari:
Representation Learning Beyond Linear Prediction Functions. 4792-4804 - Lior Yariv, Jiatao Gu, Yoni Kasten, Yaron Lipman:
Volume Rendering of Neural Implicit Surfaces. 4805-4815 - Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaïd Harchaoui:
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers. 4816-4828 - Han Shao, Tassilo Kugelstadt, Torsten Hädrich, Wojtek Palubicki, Jan Bender, Sören Pirk, Dominik L. Michels:
Accurately Solving Rod Dynamics with Graph Learning. 4829-4842 - Huy Tuan Pham, Phan-Minh Nguyen:
Limiting fluctuation and trajectorial stability of multilayer neural networks with mean field training. 4843-4855 - Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi:
Medical Dead-ends and Learning to Identify High-Risk States and Treatments. 4856-4870 - Harkirat Singh Behl, M. Pawan Kumar, Philip H. S. Torr, Krishnamurthy Dvijotham:
Overcoming the Convex Barrier for Simplex Inputs. 4871-4882 - Ashok Cutkosky
High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails. 4883-4895 - Hadi Daneshmand, Amir Joudaki, Francis R. Bach:
Batch Normalization Orthogonalizes Representations in Deep Random Networks. 4896-4906 - Navid Ardeshir, Clayton Sanford, Daniel J. Hsu:
Support vector machines and linear regression coincide with very high-dimensional features. 4907-4918 - Zhiding Yu, Rui Huang, Wonmin Byeon, Sifei Liu, Guilin Liu, Thomas M. Breuel, Anima Anandkumar, Jan Kautz:
Coupled Segmentation and Edge Learning via Dynamic Graph Propagation. 4919-4932 - David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna:
Offline RL Without Off-Policy Evaluation. 4933-4946 - Omer Elkabetz, Nadav Cohen:
Continuous vs. Discrete Optimization of Deep Neural Networks. 4947-4960 - Brian Knott, Shobha Venkataraman, Awni Y. Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten:
CrypTen: Secure Multi-Party Computation Meets Machine Learning. 4961-4973 - Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra:
Can contrastive learning avoid shortcut solutions? 4974-4986 - Gongwei Chen, Xinhang Song, Bohan Wang, Shuqiang Jiang:
See More for Scene: Pairwise Consistency Learning for Scene Classification. 4987-4999 - Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma:
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss. 5000-5011 - Kyra Gan, Su Jia, Andrew A. Li:
Greedy Approximation Algorithms for Active Sequential Hypothesis Testing. 5012-5024 - Peisong Wen, Qianqian Xu, Zhiyong Yang, Yuan He, Qingming Huang:
When False Positive is Intolerant: End-to-End Optimization with Low FPR for Multipartite Ranking. 5025-5037 - Mohammadreza Armandpour, Ali Sadeghian, Mingyuan Zhou:
Convex Polytope Trees and its Application to VAE. 5038-5051 - Naman Agarwal, Peter Kairouz, Ziyu Liu:
The Skellam Mechanism for Differentially Private Federated Learning. 5052-5064 - Yegor Klochkov, Nikita Zhivotovskiy:
Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$. 5065-5076 - Wamiq Reyaz Para, Shariq Farooq Bhat, Paul Guerrero, Tom Kelly, Niloy J. Mitra, Leonidas J. Guibas, Peter Wonka:
SketchGen: Generating Constrained CAD Sketches. 5077-5088 - Ankit Singh:
CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation. 5089-5101 - Kunho Kim, Sivakanth Gopi, Janardhan Kulkarni, Sergey Yekhanin:
Differentially Private n-gram Extraction. 5102-5111 - Joy Hsu, Jeffrey Gu, Gong Her Wu, Wah Chiu, Serena Yeung:
Capturing implicit hierarchical structure in 3D biomedical images with self-supervised hyperbolic representations. 5112-5123 - Soon Hoe Lim, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney:
Noisy Recurrent Neural Networks. 5124-5137 - Yeong-Dae Kwon, Jinho Choo, Iljoo Yoon, Minah Park, Duwon Park, Youngjune Gwon:
Matrix encoding networks for neural combinatorial optimization. 5138-5149 - Daniella Horan, Eitan Richardson, Yair Weiss:
When Is Unsupervised Disentanglement Possible? 5150-5161 - Ruizhi Deng, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann:
Continuous Latent Process Flows. 5162-5173 - Yiheng Lin, Yang Hu, Guanya Shi, Haoyuan Sun, Guannan Qu, Adam Wierman:
Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems. 5174-5185 - Timothy Nguyen, Roman Novak, Lechao Xiao, Jaehoon Lee:
Dataset Distillation with Infinitely Wide Convolutional Networks. 5186-5198 - Qi Chen, Bing Zhao, Haidong Wang, Mingqin Li, Chuanjie Liu, Zengzhong Li, Mao Yang, Jingdong Wang:
SPANN: Highly-efficient Billion-scale Approximate Nearest Neighborhood Search. 5199-5212 - Zhixing Du, Rui Zhang, Ming Chang, Xishan Zhang, Shaoli Liu, Tianshi Chen, Yunji Chen:
Distilling Object Detectors with Feature Richness. 5213-5224 - Vanessa Piccolo, Dominik Schröder:
Analysis of one-hidden-layer neural networks via the resolvent method. 5225-5235 - Tristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-Yves Oudeyer:
Grounding Spatio-Temporal Language with Transformers. 5236-5249 - Johannes von Oswald, Dominic Zhao, Seijin Kobayashi, Simon Schug, Massimo Caccia, Nicolas Zucchet, João Sacramento:
Learning where to learn: Gradient sparsity in meta and continual learning. 5250-5263 - A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Gunes Baydin:
Domain Invariant Representation Learning with Domain Density Transformations. 5264-5275 - Tao Yu, Cuiling Lan, Wenjun Zeng, Mingxiao Feng, Zhizheng Zhang, Zhibo Chen:
PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning. 5276-5289 - Lingshen He, Yuxuan Chen, Zhengyang Shen, Yiming Dong, Yisen Wang, Zhouchen Lin:
Efficient Equivariant Network. 5290-5302 - Yunhao Tang, Tadashi Kozuno, Mark Rowland, Rémi Munos, Michal Valko:
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation. 5303-5315 - Kenneth Borup, Lars Nørvang Andersen:
Even your Teacher Needs Guidance: Ground-Truth Targets Dampen Regularization Imposed by Self-Distillation. 5316-5327 - Lucas Liebenwein, Alaa Maalouf, Dan Feldman, Daniela Rus:
Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition. 5328-5344 - Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane:
Equilibrium and non-Equilibrium regimes in the learning of Restricted Boltzmann Machines. 5345-5359 - Kuno Kim, Akshat Jindal, Yang Song, Jiaming Song, Yanan Sui, Stefano Ermon:
Imitation with Neural Density Models. 5360-5372 - Zhengyang Shen, Jean Feydy, Peirong Liu, Ariel Hernán Curiale, Rubén San José Estépar, Raúl San José Estépar, Marc Niethammer:
Accurate Point Cloud Registration with Robust Optimal Transport. 5373-5389 - Alejandro Carderera, Mathieu Besançon, Sebastian Pokutta:
Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions. 5390-5401 - Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus:
Automatic Data Augmentation for Generalization in Reinforcement Learning. 5402-5415 - Shengju Qian, Hao Shao, Yi Zhu, Mu Li, Jiaya Jia:
Blending Anti-Aliasing into Vision Transformer. 5416-5429 - Théo Bodrito, Alexandre Zouaoui, Jocelyn Chanussot, Julien Mairal:
A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration. 5430-5442 - Yixin Wang, David M. Blei, John P. Cunningham:
Posterior Collapse and Latent Variable Non-identifiability. 5443-5455 - Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Dean P. Foster, Sham M. Kakade:
The Benefits of Implicit Regularization from SGD in Least Squares Problems. 5456-5468 - Alireza Fallah, Aryan Mokhtari, Asuman E. Ozdaglar:
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks. 5469-5480 - Thomas Spooner, Nelson Vadori, Sumitra Ganesh:
Factored Policy Gradients: Leveraging Structure for Efficient Learning in MOMDPs. 5481-5493 - Dmitriy Smirnov, Michaël Gharbi, Matthew Fisher, Vitor Guizilini, Alexei A. Efros, Justin M. Solomon:
MarioNette: Self-Supervised Sprite Learning. 5494-5505 - Eric Liang, Zhanghao Wu, Michael Luo, Sven Mika, Joseph E. Gonzalez, Ion Stoica:
RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem. 5506-5517 - Gal Dalal, Assaf Hallak, Steven Dalton, Iuri Frosio, Shie Mannor, Gal Chechik:
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction. 5518-5530 - Subhabrata Dutta, Tanya Gautam, Soumen Chakrabarti, Tanmoy Chakraborty:
Redesigning the Transformer Architecture with Insights from Multi-particle Dynamical Systems. 5531-5544 - Hanxun Huang, Yisen Wang, Sarah M. Erfani, Quanquan Gu, James Bailey, Xingjun Ma:
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks. 5545-5559 - Aounon Kumar, Tom Goldstein:
Center Smoothing: Certified Robustness for Networks with Structured Outputs. 5560-5575 - Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava:
Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures. 5576-5589 - Colin Conwell, David Mayo, Andrei Barbu, Michael A. Buice, George Alvarez, Boris Katz:
Neural Regression, Representational Similarity, Model Zoology & Neural Taskonomy at Scale in Rodent Visual Cortex. 5590-5607 - Duligur Ibeling, Thomas Icard:
A Topological Perspective on Causal Inference. 5608-5619 - Gregory Szép, Neil Dalchau, Attila Csikász-Nagy:
Parameter Inference with Bifurcation Diagrams. 5620-5630 - Sattar Vakili, Henry B. Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny:
Scalable Thompson Sampling using Sparse Gaussian Process Models. 5631-5643 - Mohit Bajaj, Lingyang Chu, Zi Yu Xue, Jian Pei, Lanjun Wang, Peter Cho-Ho Lam, Yong Zhang:
Robust Counterfactual Explanations on Graph Neural Networks. 5644-5655 - Adrián Csiszárik, Péter Korösi-Szabó, Ákos K. Matszangosz, Gergely Papp, Dániel Varga:
Similarity and Matching of Neural Network Representations. 5656-5668 - Federica Granese, Marco Romanelli, Daniele Gorla, Catuscia Palamidessi, Pablo Piantanida:
DOCTOR: A Simple Method for Detecting Misclassification Errors. 5669-5681 - Hao Zhu, Ke Sun, Peter Koniusz:
Contrastive Laplacian Eigenmaps. 5682-5695 - Kookjin Lee, Nathaniel Trask, Panos Stinis:
Machine learning structure preserving brackets for forecasting irreversible processes. 5696-5707 - Alexander Soen, Ke Sun:
On the Variance of the Fisher Information for Deep Learning. 5708-5719 - Xiu-Shen Wei, Yang Shen, Xuhao Sun, Han-Jia Ye, Jian Yang:
A$^2$-Net: Learning Attribute-Aware Hash Codes for Large-Scale Fine-Grained Image Retrieval. 5720-5730 - Giovanni Trappolini, Luca Cosmo, Luca Moschella, Riccardo Marin, Simone Melzi, Emanuele Rodolà:
Shape Registration in the Time of Transformers. 5731-5744 - Hyunsoo Chung, Jungtaek Kim, Boris Knyazev, Jinhwi Lee, Graham W. Taylor, Jaesik Park, Minsu Cho:
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning. 5745-5757 - Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Dissecting the Diffusion Process in Linear Graph Convolutional Networks. 5758-5769 - Lin Song, Songyang Zhang, Songtao Liu, Zeming Li, Xuming He, Hongbin Sun, Jian Sun, Nanning Zheng:
Dynamic Grained Encoder for Vision Transformers. 5770-5783 - Kento Nozawa, Issei Sato:
Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning. 5784-5797 - Sebastian Damrich, Fred A. Hamprecht:
On UMAP's True Loss Function. 5798-5809 - Po-An Wang, Ruo-Chun Tzeng, Alexandre Proutière:
Fast Pure Exploration via Frank-Wolfe. 5810-5821 - Shifeng Zhang, Ning Kang, Tom Ryder, Zhenguo Li:
iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Coder. 5822-5833 - Shizhe Chen, Pierre-Louis Guhur, Cordelia Schmid, Ivan Laptev:
History Aware Multimodal Transformer for Vision-and-Language Navigation. 5834-5847 - Feng Liu, Wenkai Xu, Jie Lu, Danica J. Sutherland:
Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data. 5848-5860 - Irene Solaiman, Christy Dennison:
Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasets. 5861-5873 - Daron Anderson, Douglas J. Leith:
The Lazy Online Subgradient Algorithm is Universal on Strongly Convex Domains. 5874-5884 - Yaroslav Ganin, Sergey Bartunov, Yujia Li, Ethan Keller, Stefano Saliceti:
Computer-Aided Design as Language. 5885-5897 - Dandan Shan, Richard E. L. Higgins, David F. Fouhey:
COHESIV: Contrastive Object and Hand Embedding Segmentation In Video. 5898-5909 - Qingzhong Ai, Lirong He, Shiyu Liu, Zenglin Xu:
ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE. 5910-5920 - Jiaming Liu, M. Salman Asif, Brendt Wohlberg, Ulugbek Kamilov:
Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition. 5921-5933 - Jin Xu, Hyunjik Kim, Thomas Rainforth, Yee Whye Teh:
Group Equivariant Subsampling. 5934-5946 - Jiangnan Cheng, Marco Pavone, Sachin Katti, Sandeep Chinchali, Ao Tang:
Data Sharing and Compression for Cooperative Networked Control. 5947-5958 - Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon:
Hyperbolic Procrustes Analysis Using Riemannian Geometry. 5959-5971 - Mi Luo, Fei Chen, Dapeng Hu, Yifan Zhang, Jian Liang, Jiashi Feng:
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data. 5972-5984 - Jialun Zhang, Salar Fattahi, Richard Y. Zhang:
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization. 5985-5996 - Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang:
Improving Contrastive Learning on Imbalanced Data via Open-World Sampling. 5997-6009 - David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le:
Searching for Efficient Transformers for Language Modeling. 6010-6022 - Max Ryabinin, Andrey Malinin, Mark J. F. Gales:
Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets. 6023-6035 - Jiashun Wang, Huazhe Xu, Medhini Narasimhan, Xiaolong Wang:
Multi-Person 3D Motion Prediction with Multi-Range Transformers. 6036-6049 - Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney:
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. 6050-6061 - Anne Draelos, Pranjal Gupta, Na Young Jun, Chaichontat Sriworarat, John M. Pearson:
Bubblewrap: Online tiling and real-time flow prediction on neural manifolds. 6062-6074 - Lirong Xia:
The Semi-Random Satisfaction of Voting Axioms. 6075-6086 - Tianchang Shen, Jun Gao, Kangxue Yin, Ming-Yu Liu, Sanja Fidler:
Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesis. 6087-6101 - Disha Shrivastava, Hugo Larochelle, Daniel Tarlow:
Learning to Combine Per-Example Solutions for Neural Program Synthesis. 6102-6114 - Zhengyu Zhao, Zhuoran Liu, Martha A. Larson:
On Success and Simplicity: A Second Look at Transferable Targeted Attacks. 6115-6128 - Guy Blanc, Jane Lange, Li-Yang Tan:
Provably efficient, succinct, and precise explanations. 6129-6141 - Yong Liu:
Refined Learning Bounds for Kernel and Approximate $k$-Means. 6142-6154 - Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu:
Learning Causal Semantic Representation for Out-of-Distribution Prediction. 6155-6170 - Maria-Luiza Vladarean, Yura Malitsky, Volkan Cevher
A first-order primal-dual method with adaptivity to local smoothness. 6171-6182 - Pan Zhou, Caiming Xiong, Xiaotong Yuan, Steven Chu-Hong Hoi:
A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning. 6183-6197 - Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani, Alejandro Ribeiro:
Adversarial Robustness with Semi-Infinite Constrained Learning. 6198-6215 - Kamile Stankeviciute, Ahmed M. Alaa, Mihaela van der Schaar:
Conformal Time-series Forecasting. 6216-6228 - Shitong Luo, Jiaqi Guan, Jianzhu Ma, Jian Peng:
A 3D Generative Model for Structure-Based Drug Design. 6229-6239 - Robert Lunde, Purnamrita Sarkar, Rachel A. Ward:
Bootstrapping the Error of Oja's Algorithm. 6240-6252 - Joe Kileel, Timo Klock, João M. Pereira:
Landscape analysis of an improved power method for tensor decomposition. 6253-6265 - Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu:
Curriculum Offline Imitating Learning. 6266-6277 - Dongkai Wang, Shiliang Zhang, Gang Hua:
Robust Pose Estimation in Crowded Scenes with Direct Pose-Level Inference. 6278-6289 - Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima:
Ising Model Selection Using $\ell_{1}$-Regularized Linear Regression: A Statistical Mechanics Analysis. 6290-6303 - Matteo Sesia, Yaniv Romano:
Conformal Prediction using Conditional Histograms. 6304-6315 - Sheng Wan, Yibing Zhan, Liu Liu, Baosheng Yu, Shirui Pan, Chen Gong:
Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels. 6316-6327 - Bohan Tang, Yiqi Zhong, Ulrich Neumann, Gang Wang, Siheng Chen, Ya Zhang:
Collaborative Uncertainty in Multi-Agent Trajectory Forecasting. 6328-6340 - Rohan Ghosh, Mehul Motani:
Network-to-Network Regularization: Enforcing Occam's Razor to Improve Generalization. 6341-6352 - Aming Wu, Suqi Zhao, Cheng Deng, Wei Liu:
Generalized and Discriminative Few-Shot Object Detection via SVD-Dictionary Enhancement. 6353-6364 - Wesley J. Maddox, Samuel Stanton, Andrew Gordon Wilson:
Conditioning Sparse Variational Gaussian Processes for Online Decision-making. 6365-6379 - Ruosi Wan, Zhanxing Zhu, Xiangyu Zhang, Jian Sun:
Spherical Motion Dynamics: Learning Dynamics of Normalized Neural Network using SGD and Weight Decay. 6380-6391 - Jiayao Zhang, Hua Wang, Weijie J. Su:
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations. 6392-6403 - Hilaf Hasson, Bernie Wang, Tim Januschowski, Jan Gasthaus:
Probabilistic Forecasting: A Level-Set Approach. 6404-6416 - Miltiadis Kofinas, Naveen Shankar Nagaraja, Efstratios Gavves:
Roto-translated Local Coordinate Frames For Interacting Dynamical Systems. 6417-6429 - Luigi Carratino, Stefano Vigogna, Daniele Calandriello, Lorenzo Rosasco:
ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions. 6430-6441 - Misha Padidar, Xinran Zhu, Leo Huang, Jacob R. Gardner, David Bindel:
Scaling Gaussian Processes with Derivative Information Using Variational Inference. 6442-6453 - Ziang Chen, Jianfeng Lu, Yulong Lu:
On the Representation of Solutions to Elliptic PDEs in Barron Spaces. 6454-6465 - Preetam Nandy, Divya Venugopalan, Chun Lo, Shaunak Chatterjee:
A/B Testing for Recommender Systems in a Two-sided Marketplace. 6466-6477 - Frances Ding, Moritz Hardt, John Miller, Ludwig Schmidt:
Retiring Adult: New Datasets for Fair Machine Learning. 6478-6490 - Paul Liu, Aviad Rubinstein, Jan Vondrák, Junyao Zhao:
Cardinality constrained submodular maximization for random streams. 6491-6502 - Aston Zhang, Yi Tay, Yikang Shen, Alvin Chan, Shuai Zhang:
Self-Instantiated Recurrent Units with Dynamic Soft Recursion. 6503-6514 - Hippolyt Ritter, Martin Kukla, Cheng Zhang, Yingzhen Li:
Sparse Uncertainty Representation in Deep Learning with Inducing Weights. 6515-6528 - Salar Fattahi, Andrés Gómez:
Scalable Inference of Sparsely-changing Gaussian Markov Random Fields. 6529-6541 - Jixuan Wang, Kuan-Chieh Wang, Frank Rudzicz, Michael Brudno:
Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation. 6542-6554 - Rishi Saket:
Learnability of Linear Thresholds from Label Proportions. 6555-6566 - Sebastian W. Ober, Laurence Aitchison:
A variational approximate posterior for the deep Wishart process. 6567-6579 - Aldo Pacchiano, Shaun Singh, Edward Chou, Alexander C. Berg, Jakob N. Foerster:
Neural Pseudo-Label Optimism for the Bank Loan Problem. 6580-6593 - Mingjie Li, Shaobo Wang, Quanshi Zhang:
Visualizing the Emergence of Intermediate Visual Patterns in DNNs. 6594-6607 - An-Chieh Cheng, Xueting Li, Min Sun, Ming-Hsuan Yang, Sifei Liu:
Learning 3D Dense Correspondence via Canonical Point Autoencoder. 6608-6620 - Jiawei Chen, Xu Tan, Yichong Leng, Jin Xu, Guihua Wen, Tao Qin, Tie-Yan Liu:
Speech-T: Transducer for Text to Speech and Beyond. 6621-6633 - Wentian Zhao, Xinxiao Wu, Jiebo Luo:
Multi-modal Dependency Tree for Video Captioning. 6634-6645 - Dachao Lin, Haishan Ye, Zhihua Zhang:
Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear Convergence. 6646-6657 - Xiuyuan Cheng, Yao Xie:
Neural Tangent Kernel Maximum Mean Discrepancy. 6658-6670 - Ke Zhang, Carl Yang, Xiaoxiao Li, Lichao Sun
Subgraph Federated Learning with Missing Neighbor Generation. 6671-6682 - Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal:
Bellman-consistent Pessimism for Offline Reinforcement Learning. 6683-6694 - Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein:
Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks. 6695-6706 - Valerii Likhosherstov, Krzysztof Marcin Choromanski, Jared Quincy Davis, Xingyou Song, Adrian Weller:
Sub-Linear Memory: How to Make Performers SLiM. 6707-6719 - David Friede, Mathias Niepert:
Efficient Learning of Discrete-Continuous Computation Graphs. 6720-6732 - Mucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John Dickerson, Furong Huang, Tom Goldstein:
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization. 6733-6746 - Guangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu:
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima. 6747-6761 - Fangzhou Luo, Xiaolin Wu, Yanhui Guo:
Functional Neural Networks for Parametric Image Restoration Problems. 6762-6775 - Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli:
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. 6776-6789 - Johannes Gasteiger, Florian Becker, Stephan Günnemann:
GemNet: Universal Directional Graph Neural Networks for Molecules. 6790-6802 - Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama:
Loss function based second-order Jensen inequality and its application to particle variational inference. 6803-6815 - Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt:
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning. 6816-6828 - Giorgi Nadiradze, Amirmojtaba Sabour, Peter Davies, Shigang Li, Dan Alistarh:
Asynchronous Decentralized SGD with Quantized and Local Updates. 6829-6842 - Jean Tarbouriech, Runlong Zhou, Simon S. Du, Matteo Pirotta, Michal Valko, Alessandro Lazaric:
Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret. 6843-6855 - Juan D. Correa, Sanghack Lee, Elias Bareinboim:
Nested Counterfactual Identification from Arbitrary Surrogate Experiments. 6856-6867 - Shirli Di-Castro Shashua, Dotan Di Castro, Shie Mannor:
Sim and Real: Better Together. 6868-6880 - Huan Ma, Zongbo Han, Changqing Zhang, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu:
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions. 6881-6893 - Xinghao Chen, Chang Xu, Minjing Dong, Chunjing Xu, Yunhe Wang:
An Empirical Study of Adder Neural Networks for Object Detection. 6894-6905 - Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson:
Does Knowledge Distillation Really Work? 6906-6919 - Olivia Watkins, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Jacob Andreas:
Teachable Reinforcement Learning via Advice Distillation. 6920-6933 - Mani Malek Esmaeili, Ilya Mironov, Karthik Prasad, Igor Shilov, Florian Tramèr
Antipodes of Label Differential Privacy: PATE and ALIBI. 6934-6945 - Shashi Kant Gupta, Mengmi Zhang, Chia-Chien Wu, Jeremy M. Wolfe, Gabriel Kreiman:
Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases. 6946-6959 - Nicolas Keriven, Alberto Bietti, Samuel Vaiter:
On the Universality of Graph Neural Networks on Large Random Graphs. 6960-6971 - Gregory Dexter, Kevin Bello, Jean Honorio
Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees. 6972-6982 - Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong:
Adversarial Attacks on Graph Classifiers via Bayesian Optimisation. 6983-6996 - Sarah Huiyi Cen, Devavrat Shah:
Regulating algorithmic filtering on social media. 6997-7011 - Chengyue Gong, Mao Ye, Qiang Liu:
argmax centroid. 7012-7024 - Shuang Ma, Zhaoyang Zeng, Daniel McDuff, Yale Song:
Contrastive Learning of Global and Local Video Representations. 7025-7040 - Boyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang:
BooVI: Provably Efficient Bootstrapped Value Iteration. 7041-7053 - Boxi Wu, Jinghui Chen, Deng Cai, Xiaofei He, Quanquan Gu:
Do Wider Neural Networks Really Help Adversarial Robustness? 7054-7067 - Stanislav Fort, Jie Ren, Balaji Lakshminarayanan:
Exploring the Limits of Out-of-Distribution Detection. 7068-7081 - Hyuck Lee, Seungjae Shin, Heeyoung Kim:
ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning. 7082-7094 - Chris Cundy, Aditya Grover, Stefano Ermon:
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery. 7095-7110 - Iulia Duta, Andrei Liviu Nicolicioiu, Marius Leordeanu:
Discovering Dynamic Salient Regions for Spatio-Temporal Graph Neural Networks. 7111-7125 - Jayadev Acharya, Clément L. Canonne, Prathamesh Mayekar, Himanshu Tyagi:
Information-constrained optimization: can adaptive processing of gradients help? 7126-7138 - Zhengzhuo Xu, Zenghao Chai, Chun Yuan:
Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective. 7139-7152 - Daniela Mihai, Jonathon S. Hare:
Learning to Draw: Emergent Communication through Sketching. 7153-7166 - Jesse J. Hagenaars, Federico Paredes-Vallés, Guido de Croon:
Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks. 7167-7179 - Bin Dai
On the Value of Infinite Gradients in Variational Autoencoder Models. 7180-7192 - Yue Wang, Shaofeng Zou:
Online Robust Reinforcement Learning with Model Uncertainty. 7193-7206 - Angtian Wang, Shenxiao Mei, Alan L. Yuille, Adam Kortylewski:
Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose. 7207-7219 - Jiashun Jin, Zheng Tracy Ke, Jiajun Liang:
Sharp Impossibility Results for Hyper-graph Testing. 7220-7231 - Yangsibo Huang, Samyak Gupta, Zhao Song, Kai Li, Sanjeev Arora:
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning. 7232-7241 - Lin Zhao, Huaqing Xiong, Yingbin Liang:
Faster Non-asymptotic Convergence for Double Q-learning. 7242-7253 - Janne H. Korhonen, Dan Alistarh:
Towards Tight Communication Lower Bounds for Distributed Optimisation. 7254-7266 - Jiong Zhang, Wei-Cheng Chang, Hsiang-Fu Yu, Inderjit S. Dhillon:
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification. 7267-7280 - Yuhui Yuan, Rao Fu, Lang Huang, Weihong Lin, Chao Zhang, Xilin Chen, Jingdong Wang:
HRFormer: High-Resolution Vision Transformer for Dense Predict. 7281-7293 - Serguei Barannikov, Ilya Trofimov, Grigorii Sotnikov, Ekaterina Trimbach, Alexander Korotin, Alexander Filippov, Evgeny Burnaev:
Manifold Topology Divergence: a Framework for Comparing Data Manifolds. 7294-7305 - Junjie Chen, Li Niu, Liu Liu, Liqing Zhang:
Weak-shot Fine-grained Classification via Similarity Transfer. 7306-7318 - Amrutha Saseendran, Kathrin Skubch, Stefan Falkner, Margret Keuper:
Shape your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders. 7319-7332 - Blake E. Woodworth, Nathan Srebro:
An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning. 7333-7345 - Hassan Saber, Pierre Ménard, Odalric-Ambrym Maillard:
Indexed Minimum Empirical Divergence for Unimodal Bandits. 7346-7356 - Abhinav Moudgil, Arjun Majumdar, Harsh Agrawal, Stefan Lee, Dhruv Batra:
SOAT: A Scene- and Object-Aware Transformer for Vision-and-Language Navigation. 7357-7367 - Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta:
A Normative and Biologically Plausible Algorithm for Independent Component Analysis. 7368-7384 - Manuel Wüthrich, Bernhard Schölkopf, Andreas Krause:
Regret Bounds for Gaussian-Process Optimization in Large Domains. 7385-7396 - Woochul Kang, Daeyeon Kim:
Deeply Shared Filter Bases for Parameter-Efficient Convolutional Neural Networks. 7397-7408 - Shinji Ito:
On Optimal Robustness to Adversarial Corruption in Online Decision Problems. 7409-7420 - Neil Gallagher, Kafui Dzirasa, David E. Carlson:
Directed Spectrum Measures Improve Latent Network Models Of Neural Populations. 7421-7435 - Gaon An, Seungyong Moon, Jang-Hyun Kim, Hyun Oh Song:
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble. 7436-7447 - Yonghoon Lee, Rina Barber:
Distribution-free inference for regression: discrete, continuous, and in between. 7448-7459 - Kelly W. Zhang, Lucas Janson, Susan A. Murphy:
Statistical Inference with M-Estimators on Adaptively Collected Data. 7460-7471 - Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang:
NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem. 7472-7483 - Chonghao Sima, Yexiang Xue:
LSH-SMILE: Locality Sensitive Hashing Accelerated Simulation and Learning. 7484-7496 - Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. 7497-7509 - Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile:
Neural Active Learning with Performance Guarantees. 7510-7521 - Ryo Sato, Mirai Tanaka, Akiko Takeda:
A Gradient Method for Multilevel Optimization. 7522-7533 - Jaehyeong Jo, Jinheon Baek, Seul Lee, Dongki Kim, Minki Kang, Sung Ju Hwang:
Edge Representation Learning with Hypergraphs. 7534-7546 - Akari Asai, Xinyan Yu, Jungo Kasai, Hanna Hajishirzi:
One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval. 7547-7560 - Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari:
LEADS: Learning Dynamical Systems that Generalize Across Environments. 7561-7573 - Emile van Krieken, Jakub M. Tomczak, Annette ten Teije:
Storchastic: A Framework for General Stochastic Automatic Differentiation. 7574-7587 - Andreas Maurer, Massimiliano Pontil:
Concentration inequalities under sub-Gaussian and sub-exponential conditions. 7588-7597 - Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu:
Variance-Aware Off-Policy Evaluation with Linear Function Approximation. 7598-7610 - Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric:
A Provably Efficient Sample Collection Strategy for Reinforcement Learning. 7611-7624 - James Robinson, Mark Herbster:
Improved Regret Bounds for Tracking Experts with Memory. 7625-7636 - Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann:
Robustness of Graph Neural Networks at Scale. 7637-7649 - Zeyu Qin, Yanbo Fan, Hongyuan Zha, Baoyuan Wu:
Random Noise Defense Against Query-Based Black-Box Attacks. 7650-7663 - Ruichu Cai, Jinjie Yuan, Boyan Xu, Zhifeng Hao:
SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL. 7664-7676 - Ming Yin, Yu Bai, Yu-Xiang Wang:
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction. 7677-7688 - Minghao Xu, Meng Qu, Bingbing Ni, Jian Tang:
Joint Modeling of Visual Objects and Relations for Scene Graph Generation. 7689-7702 - Kazuki Irie, Imanol Schlag, Róbert Csordás, Jürgen Schmidhuber:
Going Beyond Linear Transformers with Recurrent Fast Weight Programmers. 7703-7717 - Bing-Jing Hsieh, Ping-Chun Hsieh, Xi Liu:
Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization. 7718-7731 - Ilias Diakonikolas, Daniel Kane, Christos Tzamos:
Forster Decomposition and Learning Halfspaces with Noise. 7732-7744 - Joseph Pemberton, Ellen Boven, Richard Apps, Rui Ponte Costa:
Cortico-cerebellar networks as decoupling neural interfaces. 7745-7759 - Filippos Kokkinos, Iasonas Kokkinos:
To The Point: Correspondence-driven monocular 3D category reconstruction. 7760-7772 - Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh:
Proper Value Equivalence. 7773-7786 - Akash Kumar Dhaka, Alejandro Catalina, Manushi Welandawe, Michael Riis Andersen, Jonathan H. Huggins, Aki Vehtari:
Challenges and Opportunities in High Dimensional Variational Inference. 7787-7798 - David Abel, Will Dabney, Anna Harutyunyan, Mark K. Ho, Michael L. Littman, Doina Precup, Satinder Singh:
On the Expressivity of Markov Reward. 7799-7812 - Udari Madhushani, Abhimanyu Dubey, Naomi Ehrich Leonard, Alex Pentland:
One More Step Towards Reality: Cooperative Bandits with Imperfect Communication. 7813-7824 - Yiheng Lin, Guannan Qu, Longbo Huang, Adam Wierman:
Multi-Agent Reinforcement Learning in Stochastic Networked Systems. 7825-7837 - Xueqian Li, Jhony Kaesemodel Pontes, Simon Lucey:
Neural Scene Flow Prior. 7838-7851 - Mufan (Bill) Li, Mihai Nica, Daniel M. Roy:
The future is log-Gaussian: ResNets and their infinite-depth-and-width limit at initialization. 7852-7864 - Jiayuan Mao, Freda Shi, Jiajun Wu, Roger Levy, Josh Tenenbaum:
Grammar-Based Grounded Lexicon Learning. 7865-7878 - Michael Diskin, Alexey Bukhtiyarov, Max Ryabinin, Lucile Saulnier, Quentin Lhoest, Anton Sinitsin, Dmitry Popov, Dmitry V. Pyrkin, Maxim Kashirin, Alexander Borzunov, Albert Villanova del Moral, Denis Mazur, Ilia Kobelev, Yacine Jernite, Thomas Wolf, Gennady Pekhimenko:
Distributed Deep Learning In Open Collaborations. 7879-7897 - Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C. Holmes, Frank Hutter, Yee Whye Teh:
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift. 7898-7911 - Peter Macgregor, He Sun:
Finding Bipartite Components in Hypergraphs. 7912-7923 - Soojung Yang, Doyeong Hwang, Seul Lee, Seongok Ryu, Sung Ju Hwang:
Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation. 7924-7936 - Spencer Frei, Quanquan Gu:
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent. 7937-7949 - Gavin Brown, Marco Gaboardi
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation. 7950-7964 - Linfan Zhang, Arash A. Amini:
Label consistency in overfitted generalized $k$-means. 7965-7977 - Hongxin Wei, Lue Tao, Renchunzi Xie, Bo An:
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise. 7978-7992 - Davin Choo, Tommaso d'Orsi:
The Complexity of Sparse Tensor PCA. 7993-8005 - Cem Anil, Xuchan Bao:
Learning to Elect. 8006-8017 - Pierre Glaser, Michael Arbel, Arthur Gretton:
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support. 8018-8031 - Dhruv Malik, Yuanzhi Li, Pradeep Ravikumar:
When Is Generalizable Reinforcement Learning Tractable? 8032-8045 - Manjin Kim, Heeseung Kwon, Chunyu Wang, Suha Kwak, Minsu Cho:
Relational Self-Attention: What's Missing in Attention for Video Understanding. 8046-8059 - Su Lu, Han-Jia Ye, Le Gan, De-Chuan Zhan:
Towards Enabling Meta-Learning from Target Models. 8060-8071 - Ibrahim M. Alabdulmohsin, Mario Lucic:
A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models. 8072-8084 - Martin Engelcke, Oiwi Parker Jones, Ingmar Posner:
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement. 8085-8094 - Boris Hanin, Yi Sun:
How Data Augmentation affects Optimization for Linear Regression. 8095-8105 - Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel R. D. Rodrigues, Gregory W. Wornell:
An Exact Characterization of the Generalization Error for the Gibbs Algorithm. 8106-8118 - Alberto Maria Metelli, Alessio Russo, Marcello Restelli:
Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning. 8119-8132 - Atal Narayan Sahu, Aritra Dutta, Ahmed M. Abdelmoniem, Trambak Banerjee, Marco Canini, Panos Kalnis:
Rethinking gradient sparsification as total error minimization. 8133-8146 - Anindya De, Sanjeev Khanna, Huan Li, MohammadHesam NikpeySalekde:
Approximate optimization of convex functions with outlier noise. 8147-8157 - L. Elisa Celis, Anay Mehrotra, Nisheeth K. Vishnoi:
Fair Classification with Adversarial Perturbations. 8158-8171 - Aleksandr Beznosikov, Gesualdo Scutari, Alexander Rogozin, Alexander V. Gasnikov:
Distributed Saddle-Point Problems Under Data Similarity. 8172-8184 - Aryan Deshwal, Janardhan Rao Doppa:
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces. 8185-8200 - Hong-You Chen, Wei-Lun Chao:
Gradual Domain Adaptation without Indexed Intermediate Domains. 8201-8214 - Brandon Cui, Hengyuan Hu, Luis Pineda, Jakob N. Foerster:
K-level Reasoning for Zero-Shot Coordination in Hanabi. 8215-8228 - Cameron Allen, Neev Parikh, Omer Gottesman, George Konidaris:
Learning Markov State Abstractions for Deep Reinforcement Learning. 8229-8241 - Johan Bjorck, Carla P. Gomes, Kilian Q. Weinberger:
Towards Deeper Deep Reinforcement Learning with Spectral Normalization. 8242-8255 - Huaxiu Yao, Ying Wei, Long-Kai Huang, Ding Xue, Junzhou Huang, Zhenhui Li:
Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery. 8256-8268 - Nimita Shinde, Vishnu Narayanan, James Saunderson:
Memory-Efficient Approximation Algorithms for Max-k-Cut and Correlation Clustering. 8269-8281 - Manuel Dahnert, Ji Hou, Matthias Nießner, Angela Dai:
Panoptic 3D Scene Reconstruction From a Single RGB Image. 8282-8293 - Ching-Yao Chuang, Youssef Mroueh, Kristjan H. Greenewald, Antonio Torralba, Stefanie Jegelka:
Measuring Generalization with Optimal Transport. 8294-8306 - Debolina Paul, Saptarshi Chakraborty, Swagatam Das, Jason Q. Xu:
Uniform Concentration Bounds toward a Unified Framework for Robust Clustering. 8307-8319 - Yilun Du, Katie Collins, Josh Tenenbaum, Vincent Sitzmann:
Learning Signal-Agnostic Manifolds of Neural Fields. 8320-8331 - Richard Antonello, Javier S. Turek, Vy Ai Vo, Alexander Huth:
Low-dimensional Structure in the Space of Language Representations is Reflected in Brain Responses. 8332-8344 - Raymond Zhang, Richard Combes:
On the Suboptimality of Thompson Sampling in High Dimensions. 8345-8354 - Sanghyeok Chu, Dongwan Kim, Bohyung Han:
Learning Debiased and Disentangled Representations for Semantic Segmentation. 8355-8366 - Giung Nam, Jongmin Yoon, Yoonho Lee, Juho Lee:
Diversity Matters When Learning From Ensembles. 8367-8377 - Zhen Lin, Shubhendu Trivedi, Jimeng Sun:
Locally Valid and Discriminative Prediction Intervals for Deep Learning Models. 8378-8391 - Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya:
Personalized Federated Learning With Gaussian Processes. 8392-8406 - Yuan Cao, Quanquan Gu, Mikhail Belkin:
Risk Bounds for Over-parameterized Maximum Margin Classification on Sub-Gaussian Mixtures. 8407-8418 - Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan:
Implicit SVD for Graph Representation Learning. 8419-8431 - Xiong-Hui Chen, Yang Yu, Qingyang Li, Fan-Ming Luo, Zhiwei (Tony) Qin, Wenjie Shang, Jieping Ye:
Offline Model-based Adaptable Policy Learning. 8432-8443 - Kailai Sun, Zuchao Li, Hai Zhao:
Multilingual Pre-training with Universal Dependency Learning. 8444-8456 - Junyoung Byun, Woojin Lee, Jaewook Lee:
Parameter-free HE-friendly Logistic Regression. 8457-8468 - Quentin Lutz, Elie de Panafieu, Maya Stein, Alex Scott:
Active clustering for labeling training data. 8469-8480 - Chen Tang, Wei Zhan, Masayoshi Tomizuka:
Exploring Social Posterior Collapse in Variational Autoencoder for Interaction Modeling. 8481-8494 - Thanh Lam Hoang, Gabriele Picco, Yufang Hou, Young-Suk Lee, Lam M. Nguyen, Dzung T. Phan, Vanessa López, Ramón Fernandez Astudillo:
Ensembling Graph Predictions for AMR Parsing. 8495-8505 - Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli:
On the interplay between data structure and loss function in classification problems. 8506-8517 - Suhas S. Kowshik, Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli:
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems. 8518-8531 - Saurabh Garg, Yifan Wu, Alexander J. Smola, Sivaraman Balakrishnan, Zachary C. Lipton:
Mixture Proportion Estimation and PU Learning: A Modern Approach. 8532-8544 - Chenyi Zhang, Tongyang Li:
Escape saddle points by a simple gradient-descent based algorithm. 8545-8556 - Alexandra Peste, Eugenia Iofinova, Adrian Vladu, Dan Alistarh:
AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks. 8557-8570 - Andy Shih, Dorsa Sadigh, Stefano Ermon:
HyperSPNs: Compact and Expressive Probabilistic Circuits. 8571-8582 - Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby:
Scaling Vision with Sparse Mixture of Experts. 8583-8595 - Virginie Do, Sam Corbett-Davies, Jamal Atif, Nicolas Usunier:
Two-sided fairness in rankings via Lorenz dominance. 8596-8608 - Dominic Richards, Ilja Kuzborskij:
Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel. 8609-8621 - Ishan Durugkar, Mauricio Tec, Scott Niekum, Peter Stone:
Adversarial Intrinsic Motivation for Reinforcement Learning. 8622-8636 - Yongyi Guo, Dominic Coey, Mikael Konutgan, Wenting Li, Chris Schoener, Matt Goldman:
Machine Learning for Variance Reduction in Online Experiments. 8637-8648 - Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Zixuan Jiang, Ray T. Chen, David Z. Pan:
L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization. 8649-8661 - Risheng Liu, Yaohua Liu, Shangzhi Zeng, Jin Zhang:
Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond. 8662-8675 - Fabian Falck, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Chris C. Holmes:
Multi-Facet Clustering Variational Autoencoders. 8676-8690 - Nick Doudchenko, Khashayar Khosravi, Jean Pouget-Abadie, Sébastien Lahaie, Miles Lubin, Vahab S. Mirrokni, Jann Spiess, Guido Imbens:
Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls. 8691-8701 - Hadrien Pouget, Hana Chockler, Youcheng Sun, Daniel Kroening:
Ranking Policy Decisions. 8702-8713 - Minghao Chen, Kan Wu, Bolin Ni, Houwen Peng, Bei Liu, Jianlong Fu, Hongyang Chao, Haibin Ling:
Searching the Search Space of Vision Transformer. 8714-8726 - Leonardo Petrini, Alessandro Favero, Mario Geiger, Matthieu Wyart:
Relative stability toward diffeomorphisms indicates performance in deep nets. 8727-8739 - Aditya Desai, Zhaozhuo Xu, Menal Gupta, Anu Chandran, Antoine Vial-Aussavy, Anshumali Shrivastava:
Raw Nav-merge Seismic Data to Subsurface Properties with MLP based Multi-Modal Information Unscrambler. 8740-8752 - Sriram Ravula, Georgios Smyrnis, Matt Jordan, Alexandros G. Dimakis:
Inverse Problems Leveraging Pre-trained Contrastive Representations. 8753-8765 - Thibault Séjourné, François-Xavier Vialard, Gabriel Peyré:
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation. 8766-8779 - Prafulla Dhariwal, Alexander Quinn Nichol:
Diffusion Models Beat GANs on Image Synthesis. 8780-8794 - Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe:
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning. 8795-8806 - Anand Kalvit, Assaf Zeevi:
A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms. 8807-8819 - Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-Hornung, Daniel Cohen-Or:
SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization. 8820-8832 - Qingru Zhang, David Wipf, Quan Gan, Le Song:
A Biased Graph Neural Network Sampler with Near-Optimal Regret. 8833-8844 - Gabriele Farina, Tuomas Sandholm:
Equilibrium Refinement for the Age of Machines: The One-Sided Quasi-Perfect Equilibrium. 8845-8856 - Wen Shen, Qihan Ren, Dongrui Liu, Quanshi Zhang:
Interpreting Representation Quality of DNNs for 3D Point Cloud Processing. 8857-8870 - Kurtland Chua, Qi Lei, Jason D. Lee:
How Fine-Tuning Allows for Effective Meta-Learning. 8871-8884 - Lin Yang, Yu-Zhen Janice Chen, Stephen Pasteris, Mohammad H. Hajiesmaili, John C. S. Lui, Don Towsley:
Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback. 8885-8897 - Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi:
Multiple Descent: Design Your Own Generalization Curve. 8898-8912 - Abhishek Roy, Krishnakumar Balasubramanian, Murat A. Erdogdu:
On Empirical Risk Minimization with Dependent and Heavy-Tailed Data. 8913-8926 - Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade:
Gone Fishing: Neural Active Learning with Fisher Embeddings. 8927-8939 - Andi Han, Bamdev Mishra, Pratik Kumar Jawanpuria, Junbin Gao:
On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry. 8940-8953 - Huihan Yao, Ying Chen, Qinyuan Ye, Xisen Jin, Xiang Ren:
Refining Language Models with Compositional Explanations. 8954-8967 - Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang:
Going Beyond Linear RL: Sample Efficient Neural Function Approximation. 8968-8983 - Tianshi Cao, Sasha Doubov, David Acuna, Sanja Fidler:
Scalable Neural Data Server: A Data Recommender for Transfer Learning. 8984-8997 - Guillermo Ortiz-Jiménez, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard:
What can linearized neural networks actually say about generalization? 8998-9010 - Seokju Cho, Sunghwan Hong, Sangryul Jeon, Yunsung Lee, Kwanghoon Sohn, Seungryong Kim:
CATs: Cost Aggregation Transformers for Visual Correspondence. 9011-9023 - Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain:
Asynchronous Stochastic Optimization Robust to Arbitrary Delays. 9024-9035 - Robi Bhattacharjee, Kamalika Chaudhuri:
Consistent Non-Parametric Methods for Maximizing Robustness. 9036-9048 - Tao Jin, Zhou Zhao:
Generalizable Multi-linear Attention Network. 9049-9060 - Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin:
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning. 9061-9073 - Feihu Huang, Junyi Li, Heng Huang:
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients. 9074-9085 - Daniel Franzen, Michael Wand:
General Nonlinearities in SO(2)-Equivariant CNNs. 9086-9098 - Christian Horvat, Jean-Pascal Pfister:
Denoising Normalizing Flow. 9099-9111 - David Ding, Felix Hill, Adam Santoro, Malcolm Reynolds, Matt M. Botvinick:
Attention over Learned Object Embeddings Enables Complex Visual Reasoning. 9112-9124 - Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet:
Differentially Private Federated Bayesian Optimization with Distributed Exploration. 9125-9139 - Nastaran Okati, Abir De, Manuel Gomez-Rodriguez:
Differentiable Learning Under Triage. 9140-9151 - Nicolò Cesa-Bianchi, Tommaso Cesari, Yishay Mansour, Vianney Perchet:
A New Theoretical Framework for Fast and Accurate Online Decision-Making. 9152-9166 - Jiawei Zhang, Yushun Zhang, Mingyi Hong, Ruoyu Sun, Zhi-Quan Luo:
When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work. 9167-9180 - Souvik Kundu, Qirui Sun, Yao Fu, Massoud Pedram, Peter A. Beerel:
Analyzing the Confidentiality of Undistillable Teachers in Knowledge Distillation. 9181-9192 - Billy Jin, Katya Scheinberg, Miaolan Xie:
High Probability Complexity Bounds for Line Search Based on Stochastic Oracles. 9193-9203 - Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le:
Pay Attention to MLPs. 9204-9215 - Aviv Gabbay, Niv Cohen, Yedid Hoshen:
An Image is Worth More Than a Thousand Words: Towards Disentanglement in The Wild. 9216-9228 - Courtney Paquette, Elliot Paquette:
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models. 9229-9240 - Peter L. Bartlett, Sébastien Bubeck, Yeshwanth Cherapanamjeri:
Adversarial Examples in Multi-Layer Random ReLU Networks. 9241-9252 - Karim Tit, Teddy Furon, Mathias Rousset:
Efficient Statistical Assessment of Neural Network Corruption Robustness. 9253-9263 - Tobia Boschi, Matthew Reimherr, Francesca Chiaromonte:
A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression. 9264-9277 - Bogdan-Adrian Manghiuc
Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs. 9278-9289 - Olivier Veilleux, Malik Boudiaf, Pablo Piantanida, Ismail Ben Ayed:
Realistic evaluation of transductive few-shot learning. 9290-9302 - Sanghyun Hong, Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Tudor Dumitras:
Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes. 9303-9316 - Raef Bassily, Cristóbal Guzmán, Michael Menart:
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings. 9317-9329 - Minchao Wu, Michael Norrish, Christian Walder, Amir Dezfouli:
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning. 9330-9342 - Han Peng, Ge Li, Wenhan Wang, Yunfei Zhao, Zhi Jin:
Integrating Tree Path in Transformer for Code Representation. 9343-9354 - Xiangxiang Chu, Zhi Tian, Yuqing Wang, Bo Zhang, Haibing Ren, Xiaolin Wei, Huaxia Xia, Chunhua Shen:
Twins: Revisiting the Design of Spatial Attention in Vision Transformers. 9355-9366 - Ryan Theisen, Huan Wang, Lav R. Varshney, Caiming Xiong, Richard Socher:
Evaluating State-of-the-Art Classification Models Against Bayes Optimality. 9367-9377 - Ceyuan Yang, Yujun Shen, Yinghao Xu, Bolei Zhou:
Data-Efficient Instance Generation from Instance Discrimination. 9378-9390 - Dylan Slack, Anna Hilgard, Sameer Singh, Himabindu Lakkaraju:
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability. 9391-9404 - Vignesh Ram Somnath, Charlotte Bunne, Connor W. Coley, Andreas Krause, Regina Barzilay:
Learning Graph Models for Retrosynthesis Prediction. 9405-9415 - Shinsaku Sakaue, Kengo Nakamura:
Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games. 9416-9428 - Matthias Schultheis, Dominik Straub, Constantin A. Rothkopf:
Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System. 9429-9442 - Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande:
Deep Neural Networks as Point Estimates for Deep Gaussian Processes. 9443-9455 - Alessandro Favero, Francesco Cagnetta, Matthieu Wyart:
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios. 9456-9467 - Sanghack Lee, Elias Bareinboim:
Causal Identification with Matrix Equations. 9468-9479 - Róbert Busa-Fekete, Dimitris Fotakis, Emmanouil Zampetakis
Private and Non-private Uniformity Testing for Ranking Data. 9480-9492 - Yao Mu, Yuzheng Zhuang, Bin Wang, Guangxiang Zhu, Wulong Liu, Jianyu Chen, Ping Luo, Shengbo Li, Chongjie Zhang, Jianye Hao:
Model-Based Reinforcement Learning via Imagination with Derived Memory. 9493-9505 - Dor Arad Hudson, Larry Zitnick:
Compositional Transformers for Scene Generation. 9506-9520 - Yuanhao Wang, Ruosong Wang, Sham M. Kakade:
An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap. 9521-9533 - Zhenyu Wang, Ya-Li Li, Ye Guo, Shengjin Wang:
Combating Noise: Semi-supervised Learning by Region Uncertainty Quantification. 9534-9545 - Yin Zhao, Minquan Wang, Longjun Cai:
Reducing the Covariate Shift by Mirror Samples in Cross Domain Alignment. 9546-9558 - Robin Winter, Frank Noé, Djork-Arné Clevert:
Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning. 9559-9573 - Atticus Geiger, Hanson Lu, Thomas Icard, Christopher Potts:
Causal Abstractions of Neural Networks. 9574-9586 - Julien Grand-Clément, Christian Kroer:
Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving. 9587-9599 - Nishad Gothoskar, Marco F. Cusumano-Towner, Ben Zinberg, Matin Ghavamizadeh, Falk Pollok, Austin Garrett, Josh Tenenbaum, Dan Gutfreund, Vikash K. Mansinghka:
3DP3: 3D Scene Perception via Probabilistic Programming. 9600-9612 - Tahrima Rahman, Sara Rouhani, Vibhav Gogate
Novel Upper Bounds for the Constrained Most Probable Explanation Task. 9613-9624 - Zinan Lin, Vyas Sekar, Giulia Fanti:
Why Spectral Normalization Stabilizes GANs: Analysis and Improvements. 9625-9638 - Zhichun Huang, Shaojie Bai, J. Zico Kolter:
$(\textrm{Implicit})^2$: Implicit Layers for Implicit Representations. 9639-9650 - Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das:
Best Arm Identification in Contaminated Stochastic Bandits. 9651-9662 - Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E. Gonzalez, Stuart Russell:
MADE: Exploration via Maximizing Deviation from Explored Regions. 9663-9680 - Jiayu Chen, Yuanxin Zhang, Yuanfan Xu, Huimin Ma, Huazhong Yang, Jiaming Song, Yu Wang, Yi Wu:
Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problems. 9681-9693 - Junnan Li, Ramprasaath R. Selvaraju, Akhilesh Gotmare, Shafiq R. Joty, Caiming Xiong, Steven Chu-Hong Hoi:
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation. 9694-9705 - Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard S. Zemel, Alireza Makhzani:
Variational Model Inversion Attacks. 9706-9719 - Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang:
Graph Neural Networks with Adaptive Residual. 9720-9733 - Guang Zhao, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian:
Efficient Active Learning for Gaussian Process Classification by Error Reduction. 9734-9746 - Yue Wang, Shaofeng Zou, Yi Zhou:
Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation. 9747-9758 - Jacob M. Springer, Melanie Mitchell, Garrett T. Kenyon:
A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks. 9759-9773 - Tanzila Rahman, Mengyu Yang, Leonid Sigal:
TriBERT: Human-centric Audio-visual Representation Learning. 9774-9787 - Jingling Li, Mozhi Zhang, Keyulu Xu, John Dickerson, Jimmy Ba:
How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? 9788-9803 - Pranjal Awasthi, Natalie Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong:
Calibration and Consistency of Adversarial Surrogate Losses. 9804-9815 - Dilip Arumugam, Benjamin Van Roy:
The Value of Information When Deciding What to Learn. 9816-9827 - Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, Shixiang Shane Gu:
Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning. 9828-9842 - Aniketh Janardhan Reddy, Leila Wehbe:
Can fMRI reveal the representation of syntactic structure in the brain? 9843-9856 - Saber Jafarpour, Alexander Davydov, Anton V. Proskurnikov, Francesco Bullo:
Robust Implicit Networks via Non-Euclidean Contractions. 9857-9868 - Hongjiao Liu, Anna M. Plantinga, Yunhua Xiang, Michael C. Wu:
A Kernel-based Test of Independence for Cluster-correlated Data. 9869-9881 - David Bolin, Jonas Wallin:
Efficient methods for Gaussian Markov random fields under sparse linear constraints. 9882-9894 - Sebastian Jaszczur, Aakanksha Chowdhery, Afroz Mohiuddin, Lukasz Kaiser, Wojciech Gajewski, Henryk Michalewski, Jonni Kanerva:
Sparse is Enough in Scaling Transformers. 9895-9907 - Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. 9908-9922 - Mengmeng Xu, Juan-Manuel Pérez-Rúa, Xiatian Zhu, Bernard Ghanem, Brais Martínez:
Low-Fidelity Video Encoder Optimization for Temporal Action Localization. 9923-9935 - Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi:
On Provable Benefits of Depth in Training Graph Convolutional Networks. 9936-9949 - Joshua Engels, Benjamin Coleman, Anshumali Shrivastava:
Practical Near Neighbor Search via Group Testing. 9950-9962 - Kanishk Gandhi, Gala Stojnic, Brenden M. Lake, Moira R. Dillon:
Baby Intuitions Benchmark (BIB): Discerning the goals, preferences, and actions of others. 9963-9976 - Michael Poli, Stefano Massaroli, Luca Scimeca, Sanghyuk Chun, Seong Joon Oh, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg:
Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions. 9977-9989 - Andersen Man Shun Ang, Jianzhu Ma, Nianjun Liu, Kun Huang, Yijie Wang:
Fast Projection onto the Capped Simplex with Applications to Sparse Regression in Bioinformatics. 9990-9999 - Muni Sreenivas Pydi, Varun S. Jog:
The Many Faces of Adversarial Risk. 10000-10012 - Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue:
Meta-Adaptive Nonlinear Control: Theory and Algorithms. 10013-10025 - Kishor Jothimurugan, Suguman Bansal, Osbert Bastani, Rajeev Alur:
Compositional Reinforcement Learning from Logical Specifications. 10026-10039 - Matthew C. Fontaine, Stefanos Nikolaidis:
Differentiable Quality Diversity. 10040-10052 - David G. Clark, L. F. Abbott, SueYeon Chung:
Credit Assignment Through Broadcasting a Global Error Vector. 10053-10066 - Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang:
An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives. 10067-10080 - Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes:
A single gradient step finds adversarial examples on random two-layers neural networks. 10081-10091 - Jie Zhang, Song Guo, Xiaosong Ma, Haozhao Wang, Wenchao Xu, Feijie Wu:
Parameterized Knowledge Transfer for Personalized Federated Learning. 10092-10104 - Junwen Bai, Weiran Wang, Carla P. Gomes:
Contrastively Disentangled Sequential Variational Autoencoder. 10105-10118 - Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash:
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. 10119-10130 - Hugo Cui, Bruno Loureiro, Florent Krzakala
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime. 10131-10143 - Bruno Loureiro, Gabriele Sicuro, Cédric Gerbelot, Alessandro Pacco, Florent Krzakala
Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions. 10144-10157 - Ian Gallagher, Andrew Jones, Patrick Rubin-Delanchy:
Spectral embedding for dynamic networks with stability guarantees. 10158-10170 - Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger:
Infinite Time Horizon Safety of Bayesian Neural Networks. 10171-10185 - Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai:
Towards understanding retrosynthesis by energy-based models. 10186-10194 - Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian:
List-Decodable Mean Estimation in Nearly-PCA Time. 10195-10208 - Arya Akhavan, Massimiliano Pontil, Alexandre B. Tsybakov:
Distributed Zero-Order Optimization under Adversarial Noise. 10209-10220 - Sandesh Ghimire, Aria Masoomi, Jennifer G. Dy:
Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space. 10221-10233 - Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt:
Latent Matters: Learning Deep State-Space Models. 10234-10245 - Zhizhou Ren, Guangxiang Zhu, Hao Hu, Beining Han, Jianglun Chen, Chongjie Zhang:
On the Estimation Bias in Double Q-Learning. 10246-10259 - Haiyan Yin, Peng Yang, Ping Li:
Mitigating Forgetting in Online Continual Learning with Neuron Calibration. 10260-10272 - Dmitrii Avdiukhin, Grigory Yaroslavtsev:
Escaping Saddle Points with Compressed SGD. 10273-10284 - Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzcinski, Przemyslaw Spurek, Maciej Zieba:
Non-Gaussian Gaussian Processes for Few-Shot Regression. 10285-10298 - Yiqin Yang, Xiaoteng Ma, Chenghao Li, Zewu Zheng, Qiyuan Zhang, Gao Huang, Jun Yang, Qianchuan Zhao:
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning. 10299-10312 - Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian J. Ratliff:
Online Learning in Periodic Zero-Sum Games. 10313-10325 - Wenwei Zhang, Jiangmiao Pang, Kai Chen, Chen Change Loy:
K-Net: Towards Unified Image Segmentation. 10326-10338 - Bo Sun, Russell Lee, Mohammad H. Hajiesmaili, Adam Wierman, Danny H. K. Tsang:
Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems. 10339-10350 - Zhiyi Ma, Kawin Ethayarajh, Tristan Thrush, Somya Jain, Ledell Wu, Robin Jia, Christopher Potts, Adina Williams, Douwe Kiela:
Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking. 10351-10367 - Jonas Zehnder, Yue Li, Stelian Coros, Bernhard Thomaszewski:
NTopo: Mesh-free Topology Optimization using Implicit Neural Representations. 10368-10381 - Yang An, Rui Gao:
Generalization Bounds for (Wasserstein) Robust Optimization. 10382-10392 - Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii:
Faster Matchings via Learned Duals. 10393-10406 - Gergely Neu, Julia Olkhovskaya:
Online learning in MDPs with linear function approximation and bandit feedback. 10407-10417 - Minsu Kim, Jinkyoo Park, Joungho Kim:
Learning Collaborative Policies to Solve NP-hard Routing Problems. 10418-10430 - Feihu Huang, Xidong Wu, Heng Huang:
Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems. 10431-10443 - Shuang Ao, Tianyi Zhou, Guodong Long, Qinghua Lu, Liming Zhu, Jing Jiang:
CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum. 10444-10456 - Farhad Ghazvinian Zanjani, Ilia Karmanov, Hanno Ackermann, Daniel Dijkman, Simone Merlin, Max Welling, Fatih Porikli:
Modality-Agnostic Topology Aware Localization. 10457-10468 - Ziyu Wang, Yuhao Zhou, Tongzheng Ren, Jun Zhu:
Scalable Quasi-Bayesian Inference for Instrumental Variable Regression. 10469-10482 - Fergus Simpson, Ian Davies, Vidhi Lalchand, Alessandro Vullo, Nicolas Durrande, Carl Edward Rasmussen:
Kernel Identification Through Transformers. 10483-10495 - Gaurav Yengera, Rati Devidze, Parameswaran Kamalaruban, Adish Singla:
Curriculum Design for Teaching via Demonstrations: Theory and Applications. 10496-10509 - Ellen Vitercik, Tom Yan:
Revenue maximization via machine learning with noisy data. 10510-10523 - Jinming Cui, Chaochao Chen, Lingjuan Lyu, Carl Yang, Li Wang:
Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation. 10524-10534 - Amin Karbasi, Vahab S. Mirrokni, Mohammad Shadravan:
Parallelizing Thompson Sampling. 10535-10548 - Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas:
Dynamic Causal Bayesian Optimization. 10549-10560 - Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke, Matteo Pirotta:
Local Differential Privacy for Regret Minimization in Reinforcement Learning. 10561-10573 - Mycal Tucker, Huao Li, Siddharth Agrawal, Dana Hughes, Katia P. Sycara, Michael Lewis, Julie A. Shah:
Emergent Discrete Communication in Semantic Spaces. 10574-10586 - Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith B. Hengen, Michal Valko, Eva L. Dyer:
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity. 10587-10599 - Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Equivariant Manifold Flows. 10600-10612 - Kristopher T. Jensen, Ta-Chu Kao, Jasmine Stone, Guillaume Hennequin:
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models. 10613-10626 - Jingyu Zhao, Yanwen Fang, Guodong Li:
Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer Aggregation. 10627-10640 - Frank Ruis, Gertjan J. Burghouts, Doina Bucur:
Independent Prototype Propagation for Zero-Shot Compositionality. 10641-10653 - Di Jin, Zhizhi Yu, Cuiying Huo, Rui Wang, Xiao Wang, Dongxiao He, Jiawei Han:
Universal Graph Convolutional Networks. 10654-10664 - Pouya Bashivan, Reza Bayat, Adam Ibrahim, Kartik Ahuja, Mojtaba Faramarzi, Touraj Laleh, Blake A. Richards, Irina Rish:
Adversarial Feature Desensitization. 10665-10677 - Piotr Indyk, Tal Wagner, David P. Woodruff:
Few-Shot Data-Driven Algorithms for Low Rank Approximation. 10678-10690 - Mark Boss, Varun Jampani, Raphael Braun, Ce Liu, Jonathan T. Barron, Hendrik P. A. Lensch:
Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition. 10691-10704 - Morgane Austern, Vasilis Syrgkanis:
Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection. 10705-10717 - Binghui Peng:
Dynamic influence maximization. 10718-10731 - Zakaria Mhammedi:
Risk Monotonicity in Statistical Learning. 10732-10744 - Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D. Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine:
Information is Power: Intrinsic Control via Information Capture. 10745-10758 - Guilherme A. Potje, Renato Martins, Felipe C. Chamone, Erickson R. Nascimento:
Extracting Deformation-Aware Local Features by Learning to Deform. 10759-10771 - Nanbo Li, Muhammad Ahmed Raza, Wenbin Hu, Zhaole Sun, Robert B. Fisher:
Object-Centric Representation Learning with Generative Spatial-Temporal Factorization. 10772-10783 - Zhenghao Peng, Quanyi Li, Ka-Ming Hui, Chunxiao Liu, Bolei Zhou:
Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization. 10784-10797 - Paul Micaelli, Amos J. Storkey:
Gradient-based Hyperparameter Optimization Over Long Horizons. 10798-10809 - Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford:
Stochastic Bias-Reduced Gradient Methods. 10810-10822 - Kevin Xia, Kai-Zhan Lee, Yoshua Bengio, Elias Bareinboim:
The Causal-Neural Connection: Expressiveness, Learnability, and Inference. 10823-10836 - Xinyi Xu, Zhaoxuan Wu, Chuan Sheng Foo, Bryan Kian Hsiang Low:
Validation Free and Replication Robust Volume-based Data Valuation. 10837-10848 - Liyu Chen, Mehdi Jafarnia-Jahromi, Rahul Jain, Haipeng Luo:
Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path. 10849-10861 - Samuel Deng, Sanjam Garg
A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks. 10862-10875 - Robert J. N. Baldock, Hartmut Maennel, Behnam Neyshabur:
Deep Learning Through the Lens of Example Difficulty. 10876-10889 - Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu:
R-Drop: Regularized Dropout for Neural Networks. 10890-10905 - Wei Tan, Lan Du, Wray L. Buntine:
Diversity Enhanced Active Learning with Strictly Proper Scoring Rules. 10906-10918 - Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup Moon:
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning. 10919-10930 - Behnoush Khavari, Guillaume Rabusseau:
Lower and Upper Bounds on the Pseudo-Dimension of Tensor Network Models. 10931-10943 - Yu Huang, Chenzhuang Du, Zihui Xue, Xuanyao Chen, Hang Zhao, Longbo Huang:
What Makes Multi-Modal Learning Better than Single (Provably). 10944-10956 - Guojun Zhang, Han Zhao, Yaoliang Yu, Pascal Poupart:
Quantifying and Improving Transferability in Domain Generalization. 10957-10970 - Youngseog Chung, Willie Neiswanger, Ian Char, Jeff Schneider:
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification. 10971-10984 - Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf:
Dynamic Inference with Neural Interpreters. 10985-10998 - Kirill Struminsky, Artyom Gadetsky, Denis Rakitin, Danil Karpushkin, Dmitry P. Vetrov:
Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces. 10999-11011 - Greg Ver Steeg, Aram Galstyan:
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling. 11012-11025 - Dongqi Cai, Anbang Yao, Yurong Chen:
Dynamic Normalization and Relay for Video Action Recognition. 11026-11040 - Arjun R. Akula, Varun Jampani, Soravit Changpinyo, Song-Chun Zhu:
Robust Visual Reasoning via Language Guided Neural Module Networks. 11041-11053 - Ethan Perez, Douwe Kiela, Kyunghyun Cho:
True Few-Shot Learning with Language Models. 11054-11070 - Romain Camilleri, Zhihan Xiong, Maryam Fazel, Lalit Jain, Kevin G. Jamieson:
Selective Sampling for Online Best-arm Identification. 11071-11082 - Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song:
Multi-task Learning of Order-Consistent Causal Graphs. 11083-11095 - Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, Jing Tang:
Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer. 11096-11107 - Keisuke Fujii, Naoya Takeishi, Kazushi Tsutsui, Emyo Fujioka, Nozomi Nishiumi, Ryoya Tanaka, Mika Fukushiro, Kaoru Ide, Hiroyoshi Kohno, Ken Yoda, Susumu Takahashi, Shizuko Hiryu, Yoshinobu Kawahara:
Learning interaction rules from multi-animal trajectories via augmented behavioral models. 11108-11122 - Guofeng Cui, He Zhu:
Differentiable Synthesis of Program Architectures. 11123-11135 - Leonard Berrada, Sumanth Dathathri, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Jonathan Uesato, Sven Gowal, M. Pawan Kumar:
Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications. 11136-11147 - Aviv Rosenberg, Yishay Mansour:
Oracle-Efficient Regret Minimization in Factored MDPs with Unknown Structure. 11148-11159 - Nicholas Krämer, Philipp Hennig:
Linear-Time Probabilistic Solution of Boundary Value Problems. 11160-11171 - Mohammad Rostami:
Lifelong Domain Adaptation via Consolidated Internal Distribution. 11172-11183 - Jamie Kang, Faidra Monachou, Moran Koren, Itai Ashlagi:
Counterbalancing Learning and Strategic Incentives in Allocation Markets. 11184-11195 - Sungyong Seo, Sercan Ö. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister:
Controlling Neural Networks with Rule Representations. 11196-11207 - Etienne Boursier, Tristan Garrec, Vianney Perchet, Marco Scarsini:
Making the most of your day: online learning for optimal allocation of time. 11208-11219 - Karan Singhal, Hakim Sidahmed, Zachary Garrett, Shanshan Wu, John Rush, Sushant Prakash:
Federated Reconstruction: Partially Local Federated Learning. 11220-11232 - Yanjun Han, Soham Jana, Yihong Wu:
Optimal prediction of Markov chains with and without spectral gap. 11233-11246 - Chaehwan Song, Ali Ramezani-Kebrya, Thomas Pethick, Armin Eftekhari, Volkan Cevher
Subquadratic Overparameterization for Shallow Neural Networks. 11247-11259 - Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J. Smola:
Continuous Doubly Constrained Batch Reinforcement Learning. 11260-11273 - Qitian Wu, Rui Gao, Hongyuan Zha:
Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators. 11274-11286 - Arash Vahdat, Karsten Kreis, Jan Kautz:
Score-based Generative Modeling in Latent Space. 11287-11302 - Laura Manduchi, Kieran Chin-Cheong, Holger Michel, Sven Wellmann, Julia E. Vogt:
Deep Conditional Gaussian Mixture Model for Constrained Clustering. 11303-11314 - Mengde Xu, Zheng Zhang, Fangyun Wei, Yutong Lin, Yue Cao, Stephen Lin, Han Hu, Xiang Bai:
Bootstrap Your Object Detector via Mixed Training. 11315-11325 - Gabriel Koch Ocker, Michael A. Buice:
Tensor decompositions of higher-order correlations by nonlinear Hebbian plasticity. 11326-11339 - Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger:
Online Adaptation to Label Distribution Shift. 11340-11351 - Vivswan Shitole, Fuxin Li, Minsuk Kahng, Prasad Tadepalli, Alan Fern:
One Explanation is Not Enough: Structured Attention Graphs for Image Classification. 11352-11363 - Zhaozhi Qian, William R. Zame, Lucas M. Fleuren, Paul W. G. Elbers, Mihaela van der Schaar:
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression. 11364-11383 - Xuefan Zha, Wentao Zhu, Xun Lv, Sen Yang, Ji Liu:
Shifted Chunk Transformer for Spatio-Temporal Representational Learning. 11384-11396 - Hamza Fawzi, Harry Goulbourne:
Faster proximal algorithms for matrix optimization using Jacobi-based eigenvalue methods. 11397-11408 - Josh Rozner, Christopher Potts, Kyle Mahowald:
Decrypting Cryptic Crosswords: Semantically Complex Wordplay Puzzles as a Target for NLP. 11409-11421 - Anastasia Koloskova, Tao Lin, Sebastian U. Stich:
An Improved Analysis of Gradient Tracking for Decentralized Machine Learning. 11422-11435 - Steven Hansen, Guillaume Desjardins, Kate Baumli, David Warde-Farley, Nicolas Heess, Simon Osindero, Volodymyr Mnih:
Entropic Desired Dynamics for Intrinsic Control. 11436-11448 - Yan-Bo Lin, Hung-Yu Tseng, Hsin-Ying Lee, Yen-Yu Lin, Ming-Hsuan Yang:
Exploring Cross-Video and Cross-Modality Signals for Weakly-Supervised Audio-Visual Video Parsing. 11449-11461 - Noah Golowich, Roi Livni:
Littlestone Classes are Privately Online Learnable. 11462-11473 - Vincent Adam, Paul E. Chang, Mohammad Emtiyaz Khan, Arno Solin:
Dual Parameterization of Sparse Variational Gaussian Processes. 11474-11486 - Chu Zhou, Minggui Teng, Yufei Han, Chao Xu, Boxin Shi:
Learning to dehaze with polarization. 11487-11500 - Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn:
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning. 11501-11516 - George Zhang, Jingjing Qian, Jun Chen, Ashish Khisti:
Universal Rate-Distortion-Perception Representations for Lossy Compression. 11517-11529 - Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux:
What's a good imputation to predict with missing values? 11530-11540 - Ben Eysenbach, Sergey Levine, Ruslan Salakhutdinov:
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification. 11541-11552 - Jonas Gehring, Gabriel Synnaeve, Andreas Krause, Nicolas Usunier:
Hierarchical Skills for Efficient Exploration. 11553-11564 - Phil Chen, Masha Itkina, Ransalu Senanayake, Mykel J. Kochenderfer:
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models. 11565-11576 - Siddharth Mitra, Moran Feldman, Amin Karbasi:
Submodular + Concave. 11577-11591 - Angela F. Gao, Jorge C. Castellanos, Yisong Yue, Zachary E. Ross, Katherine L. Bouman:
DeepGEM: Generalized Expectation-Maximization for Blind Inversion. 11592-11603 - Kai Shen, Lingfei Wu, Siliang Tang, Yueting Zhuang, Zhen He, Zhuoye Ding, Yun Xiao, Bo Long:
Learning to Generate Visual Questions with Noisy Supervision. 11604-11617 - Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert Nowak:
Pure Exploration in Kernel and Neural Bandits. 11618-11630 - Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz:
Numerical Composition of Differential Privacy. 11631-11642 - Tung Mai, Cameron Musco, Anup Rao:
Coresets for Classification - Simplified and Strengthened. 11643-11654 - Aadil Oufkir, Omar Fawzi, Nicolas Flammarion, Aurélien Garivier:
Sequential Algorithms for Testing Closeness of Distributions. 11655-11664 - Kirill Shevkunov, Liudmila Prokhorenkova:
Overlapping Spaces for Compact Graph Representations. 11665-11677 - Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin:
Hyperparameter Tuning is All You Need for LISTA. 11678-11689 - Marcelo Arenas, Daniel Báez, Pablo Barceló, Jorge Pérez, Bernardo Subercaseaux:
Foundations of Symbolic Languages for Model Interpretability. 11690-11701 - Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell:
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. 11702-11716 - Colin Bredenberg, Benjamin Lyo, Eero P. Simoncelli, Cristina Savin:
Impression learning: Online representation learning with synaptic plasticity. 11717-11729 - Roland S. Zimmermann, Judy Borowski, Robert Geirhos, Matthias Bethge, Thomas S. A. Wallis, Wieland Brendel:
How Well do Feature Visualizations Support Causal Understanding of CNN Activations? 11730-11744 - Ruihan Wu, Chuan Guo, Awni Y. Hannun, Laurens van der Maaten:
Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems. 11745-11756 - Chen Li, Gim Hee Lee:
Coarse-to-fine Animal Pose and Shape Estimation. 11757-11768 - Jaeho Lee, Jihoon Tack, Namhoon Lee, Jinwoo Shin:
Meta-Learning Sparse Implicit Neural Representations. 11769-11780 - Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang:
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation. 11781-11794 - Nicolas Perez Nieves, Dan F. M. Goodman:
Sparse Spiking Gradient Descent. 11795-11808 - Deng-Bao Wang, Lei Feng, Min-Ling Zhang:
Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence. 11809-11820 - Gaurang Sriramanan, Sravanti Addepalli, Arya Baburaj, Venkatesh Babu R.:
Towards Efficient and Effective Adversarial Training. 11821-11833 - Ting Chen, Calvin Luo, Lala Li:
Intriguing Properties of Contrastive Losses. 11834-11845 - Jie Lei, Tamara L. Berg, Mohit Bansal:
Detecting Moments and Highlights in Videos via Natural Language Queries. 11846-11858 - Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui:
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees. 11859-11869 - Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause, Florian Dörfler:
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems. 11870-11882 - John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson L. Garfinkel, Daniel Kifer, Philip Leclerc, William Sexton, Ashley Simpson, Christine Task, Pavel Zhuravlev:
An Uncertainty Principle is a Price of Privacy-Preserving Microdata. 11883-11895 - Ashudeep Singh, David Kempe, Thorsten Joachims:
Fairness in Ranking under Uncertainty. 11896-11908 - James Queeney, Yannis Paschalidis, Christos G. Cassandras:
Generalized Proximal Policy Optimization with Sample Reuse. 11909-11919 - Gongfan Fang, Yifan Bao, Jie Song, Xinchao Wang, Donglin Xie, Chengchao Shen, Mingli Song:
Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data. 11920-11932 - Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, Sanjiv Kumar:
Batch Active Learning at Scale. 11933-11944 - Jingjing Li, Wei Ji, Qi Bi, Cheng Yan, Miao Zhang, Yongri Piao, Huchuan Lu, Li Cheng:
Joint Semantic Mining for Weakly Supervised RGB-D Salient Object Detection. 11945-11959 - Yulin Wang, Rui Huang, Shiji Song, Zeyi Huang, Gao Huang:
Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition. 11960-11973 - Thong Nguyen, Anh Tuan Luu:
Contrastive Learning for Neural Topic Model. 11974-11986 - Tadashi Kozuno, Pierre Ménard, Rémi Munos, Michal Valko:
Learning in two-player zero-sum partially observable Markov games with perfect recall. 11987-11998 - Jongmin Lee, Chanwoo Park, Ernest K. Ryu:
A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast. 11999-12012 - Despoina Paschalidou, Amlan Kar, Maria Shugrina, Karsten Kreis, Andreas Geiger, Sanja Fidler:
ATISS: Autoregressive Transformers for Indoor Scene Synthesis. 12013-12026 - Hassan Dbouk, Naresh R. Shanbhag:
Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks. 12027-12039 - Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert:
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning. 12040-12051 - Xinran Gu, Kaixuan Huang, Jingzhao Zhang, Longbo Huang:
Fast Federated Learning in the Presence of Arbitrary Device Unavailability. 12052-12064 - Vishnu Veerathu, Arun Rajkumar:
On The Structure of Parametric Tournaments with Application to Ranking from Pairwise Comparisons. 12065-12076 - Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, José M. Álvarez, Ping Luo:
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers. 12077-12090 - Mengnan Du, Subhabrata Mukherjee, Guanchu Wang, Ruixiang Tang, Ahmed Hassan Awadallah, Xia Ben Hu:
Fairness via Representation Neutralization. 12091-12103 - Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Residual Relaxation for Multi-view Representation Learning. 12104-12115 - Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy:
Do Vision Transformers See Like Convolutional Neural Networks? 12116-12128 - Ali Taghibakhshi, Scott P. MacLachlan, Luke N. Olson, Matthew West:
Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning. 12129-12140 - Wenqing Zheng, Qiangqiang Guo, Hao Yang, Peihao Wang, Zhangyang Wang:
Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systems. 12141-12153 - Jonathan Crabbé, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar:
Explaining Latent Representations with a Corpus of Examples. 12154-12166 - Aran Nayebi, Alexander Attinger, Malcolm Campbell, Kiah Hardcastle, Isabel Low, Caitlin S. Mallory, Gabriel Mel, Ben Sorscher, Alex H. Williams, Surya Ganguli, Lisa M. Giocomo, Daniel L. K. Yamins:
Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks. 12167-12179 - Robert A. Vandermeulen, Antoine Ledent:
Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation. 12180-12193 - HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim:
Multi-View Representation Learning via Total Correlation Objective. 12194-12207 - Bei Peng, Tabish Rashid, Christian Schröder de Witt, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson:
FACMAC: Factored Multi-Agent Centralised Policy Gradients. 12208-12221 - Wenbo Guo, Xian Wu, Usmann Khan
EDGE: Explaining Deep Reinforcement Learning Policies. 12222-12236 - Michael McCabe, Jed Brown:
Learning to Assimilate in Chaotic Dynamical Systems. 12237-12250 - Sangwoo Mo, Hyunwoo Kang, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin:
Object-aware Contrastive Learning for Debiased Scene Representation. 12251-12264 - Xuefei Ning, Changcheng Tang, Wenshuo Li, Zixuan Zhou, Shuang Liang, Huazhong Yang, Yu Wang:
Evaluating Efficient Performance Estimators of Neural Architectures. 12265-12277 - Shih-Yang Su, Frank Yu, Michael Zollhöfer, Helge Rhodin:
A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose. 12278-12291 - Matthew Reimherr, Karthik Bharath, Carlos Soto:
Differential Privacy Over Riemannian Manifolds. 12292-12303 - Rishi Sonthalia, Greg Van Buskirk, Benjamin Raichel, Anna C. Gilbert:
How can classical multidimensional scaling go wrong? 12304-12315 - Yushi Bai, Zhitao Ying, Hongyu Ren, Jure Leskovec:
Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones. 12316-12327 - Shiao Liu, Yunfei Yang, Jian Huang, Yuling Jiao, Yang Wang:
Non-asymptotic Error Bounds for Bidirectional GANs. 12328-12339 - Songyuan Zhang, Zhangjie Cao, Dorsa Sadigh, Yanan Sui:
Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality. 12340-12350 - Zachary Markovich:
Answering Complex Causal Queries With the Maximum Causal Set Effect. 12351-12361 - Haoyang Cao, Samuel N. Cohen, Lukasz Szpruch:
Identifiability in inverse reinforcement learning. 12362-12373 - Jonathan Schmidt, Nicholas Krämer, Philipp Hennig:
A Probabilistic State Space Model for Joint Inference from Differential Equations and Data. 12374-12385 - Julian G. Zilly, Alessandro Achille, Andrea Censi, Emilio Frazzoli:
On Plasticity, Invariance, and Mutually Frozen Weights in Sequential Task Learning. 12386-12399 - Guanlin Liu, Lifeng Lai:
Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learning. 12400-12410 - Kimia Nadjahi, Alain Durmus, Pierre E. Jacob, Roland Badeau, Umut Simsekli:
Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections. 12411-12424 - Charles Vorbach, Ramin M. Hasani, Alexander Amini, Mathias Lechner, Daniela Rus:
Causal Navigation by Continuous-time Neural Networks. 12425-12440 - Sen Na:
Global Convergence of Online Optimization for Nonlinear Model Predictive Control. 12441-12453 - Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling:
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions. 12454-12465 - Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh:
Learning with User-Level Privacy. 12466-12479 - Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis:
Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence. 12480-12492 - Mandela Patrick, Dylan Campbell, Yuki M. Asano, Ishan Misra, Florian Metze, Christoph Feichtenhofer, Andrea Vedaldi, João F. Henriques:
Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers. 12493-12506 - Brendan O'Donoghue, Tor Lattimore:
Variational Bayesian Optimistic Sampling. 12507-12519 - Xiong-Hui Chen, Shengyi Jiang, Feng Xu, Zongzhang Zhang, Yang Yu:
Cross-modal Domain Adaptation for Cost-Efficient Visual Reinforcement Learning. 12520-12532 - Abhishek Sinha, Jiaming Song, Chenlin Meng, Stefano Ermon:
D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation. 12533-12548 - Matthew McLeod, Chunlok Lo, Matthew Schlegel, Andrew Jacobsen, Raksha Kumaraswamy, Martha White, Adam White:
Continual Auxiliary Task Learning. 12549-12562 - Yunxiang Zhang, Xiangyu Zhang, Peter I. Frazier:
Two-step lookahead Bayesian optimization with inequality constraints. 12563-12575 - Kareem Amin, Giulia DeSalvo, Afshin Rostamizadeh:
Learning with Labeling Induced Abstentions. 12576-12586 - Mattia Atzeni, Jasmina Bogojeska
SQALER: Scaling Question Answering by Decoupling Multi-Hop and Logical Reasoning. 12587-12599 - Abdulkadir Canatar, Blake Bordelon, Cengiz Pehlevan:
Out-of-Distribution Generalization in Kernel Regression. 12600-12612 - Jingwei Sun, Ang Li, Louis DiValentin, Amin Hassanzadeh, Yiran Chen, Hai Li:
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective. 12613-12624 - Yi-Shan Wu, Andrés R. Masegosa, Stephan Sloth Lorenzen, Christian Igel, Yevgeny Seldin:
Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote. 12625-12636 - Pradyumna Reddy, Zhifei Zhang, Zhaowen Wang, Matthew Fisher, Hailin Jin, Niloy J. Mitra:
A Multi-Implicit Neural Representation for Fonts. 12637-12647 - Jia-Heng Tang, Weikai Chen, Jie Yang, Bo Wang, Songrun Liu, Bo Yang, Lin Gao:
OctField: Hierarchical Implicit Functions for 3D Modeling. 12648-12660 - Jonas M. Kübler, Simon Buchholz, Bernhard Schölkopf:
The Inductive Bias of Quantum Kernels. 12661-12673 - Shashank Rajput, Kartik Sreenivasan, Dimitris S. Papailiopoulos, Amin Karbasi:
An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks. 12674-12685 - Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville:
Pretraining Representations for Data-Efficient Reinforcement Learning. 12686-12699 - Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski:
Universal Approximation Using Well-Conditioned Normalizing Flows. 12700-12711 - Zhiyuan Li
On the Validity of Modeling SGD with Stochastic Differential Equations (SDEs). 12712-12725 - Dominik Peters, Grzegorz Pierczynski, Piotr Skowron:
Proportional Participatory Budgeting with Additive Utilities. 12726-12737 - Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann:
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect. 12738-12748 - Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang:
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? 12749-12760 - Raghavendra Addanki, Shiva Prasad Kasiviswanathan:
Collaborative Causal Discovery with Atomic Interventions. 12761-12773 - Adam Kalai, Varun Kanade:
Towards optimally abstaining from prediction with OOD test examples. 12774-12785 - Michael S. Ryoo, A. J. Piergiovanni, Anurag Arnab, Mostafa Dehghani, Anelia Angelova:
TokenLearner: Adaptive Space-Time Tokenization for Videos. 12786-12797 - Xiaowu Dai, Michael I. Jordan:
Learning in Multi-Stage Decentralized Matching Markets. 12798-12809 - Quentin Mérigot, Filippo Santambrogio, Clément Sarrazin:
Non-asymptotic convergence bounds for Wasserstein approximation using point clouds. 12810-12821 - Mo Yu, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola:
Understanding Interlocking Dynamics of Cooperative Rationalization. 12822-12835 - Anindya Sarkar, Anirban Sarkar, Sowrya Gali, Vineeth N. Balasubramanian:
Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach. 12836-12848 - Ted Moskovitz, Jack Parker-Holder, Aldo Pacchiano, Michael Arbel, Michael I. Jordan:
Tactical Optimism and Pessimism for Deep Reinforcement Learning. 12849-12863 - Siyuan Zhang, Nan Jiang:
Towards Hyperparameter-free Policy Selection for Offline Reinforcement Learning. 12864-12875 - Samuel Horváth, Stefanos Laskaridis, Mário Almeida, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane:
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout. 12876-12889 - Ming Yin, Yu-Xiang Wang:
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings. 12890-12903 - Zhibo Zhu, Ziqi Liu, Ge Jin, Zhiqiang Zhang, Lei Chen, Jun Zhou, Jianyong Zhou:
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data. 12904-12916 - Fangrui Lv, Jian Liang, Kaixiong Gong, Shuang Li, Chi Harold Liu, Han Li, Di Liu, Guoren Wang:
Pareto Domain Adaptation. 12917-12929 - Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals. 12930-12942 - Samarth Sinha, Adji Bousso Dieng:
Consistency Regularization for Variational Auto-Encoders. 12943-12954 - Grady Daniels, Tyler Maunu, Paul Hand:
Score-based Generative Neural Networks for Large-Scale Optimal Transport. 12955-12965 - Stefano Teso, Andrea Bontempelli, Fausto Giunchiglia, Andrea Passerini:
Interactive Label Cleaning with Example-based Explanations. 12966-12977 - Kaifeng Lyu, Zhiyuan Li
Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias. 12978-12991 - Qihang Yu, Yingda Xia, Yutong Bai, Yongyi Lu, Alan L. Yuille, Wei Shen:
Glance-and-Gaze Vision Transformer. 12992-13003 - Haixiang Zhang, Zeyu Zheng, Javad Lavaei:
Stochastic $L^\natural$-convex Function Minimization. 13004-13018 - Liang Hou, Huawei Shen, Qi Cao, Xueqi Cheng:
Self-Supervised GANs with Label Augmentation. 13019-13031 - Songyou Peng, Chiyu Jiang, Yiyi Liao, Michael Niemeyer, Marc Pollefeys, Andreas Geiger:
Shape As Points: A Differentiable Poisson Solver. 13032-13044 - Tim G. J. Rudner, Vitchyr Pong, Rowan McAllister, Yarin Gal, Sergey Levine:
Outcome-Driven Reinforcement Learning via Variational Inference. 13045-13058 - Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David D. Cox, Yingyan Lin:
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks. 13059-13072 - Xu Luo, Longhui Wei, Liangjian Wen, Jinrong Yang, Lingxi Xie, Zenglin Xu, Qi Tian:
Rectifying the Shortcut Learning of Background for Few-Shot Learning. 13073-13085 - Devendra Singh Chaplot, Murtaza Dalal, Saurabh Gupta, Jitendra Malik, Ruslan Salakhutdinov:
SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency. 13086-13098 - Kimon Antonakopoulos, Thomas Pethick, Ali Kavis, Panayotis Mertikopoulos, Volkan Cevher
Sifting through the noise: Universal first-order methods for stochastic variational inequalities. 13099-13111 - Jingfeng Wu, Vladimir Braverman, Lin Yang
Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning. 13112-13124 - Jeremy Seeman, Matthew Reimherr, Aleksandra B. Slavkovic:
Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms. 13125-13136 - Runtao Liu, Zhirong Wu, Stella X. Yu, Stephen Lin:
The Emergence of Objectness: Learning Zero-shot Segmentation from Videos. 13137-13152 - Tao Wang, Jianfeng Zhang, Yujun Cai, Shuicheng Yan, Jiashi Feng:
Direct Multi-view Multi-person 3D Pose Estimation. 13153-13164 - Zhaowen Li, Zhiyang Chen, Fan Yang, Wei Li, Yousong Zhu, Chaoyang Zhao, Rui Deng, Liwei Wu, Rui Zhao, Ming Tang, Jinqiao Wang:
MST: Masked Self-Supervised Transformer for Visual Representation. 13165-13176 - Martino Bernasconi de Luca, Federico Cacciamani, Simone Fioravanti, Nicola Gatti, Alberto Marchesi, Francesco Trovò:
Exploiting Opponents Under Utility Constraints in Sequential Games. 13177-13188 - Antonio Vergari, YooJung Choi
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference. 13189-13201 - Tim Dockhorn, Yaoliang Yu, Eyyüb Sari, Mahdi Zolnouri, Vahid Partovi Nia:
Demystifying and Generalizing BinaryConnect. 13202-13216 - Alek Dimitriev, Mingyuan Zhou:
CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator. 13217-13229 - Ze Wang, Zichen Miao, Xiantong Zhen, Qiang Qiu:
Learning to Learn Dense Gaussian Processes for Few-Shot Learning. 13230-13241 - Zahra Kadkhodaie, Eero P. Simoncelli:
Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser. 13242-13254 - Minjing Dong, Yunhe Wang, Xinghao Chen, Chang Xu:
Towards Stable and Robust AdderNets. 13255-13265 - Zhanghao Wu, Paras Jain, Matthew A. Wright, Azalia Mirhoseini, Joseph E. Gonzalez, Ion Stoica:
Representing Long-Range Context for Graph Neural Networks with Global Attention. 13266-13279 - Dirk van der Hoeven, Federico Fusco, Nicolò Cesa-Bianchi:
Beyond Bandit Feedback in Online Multiclass Classification. 13280-13291 - Dae Young Park, Moon-Hyun Cha, Changwook Jeong, Daesin Kim, Bohyung Han:
Learning Student-Friendly Teacher Networks for Knowledge Distillation. 13292-13303 - Jingyu Yang, Sheng Shen, Huanjing Yue, Kun Li:
Implicit Transformer Network for Screen Content Image Continuous Super-Resolution. 13304-13315 - Jeff Pool, Chong Yu:
Channel Permutations for N: M Sparsity. 13316-13327 - Jiwen Zhang, Zhongyu Wei, Jianqing Fan, Jiajie Peng:
Curriculum Learning for Vision-and-Language Navigation. 13328-13339 - Maryam Negahbani, Deeparnab Chakrabarty:
Better Algorithms for Individually Fair k-Clustering. 13340-13351 - Sukjun Hwang, Miran Heo, Seoung Wug Oh, Seon Joo Kim:
Video Instance Segmentation using Inter-Frame Communication Transformers. 13352-13363 - Li Wang, Li Zhang, Yi Zhu, Zhi Zhang, Tong He, Mu Li, Xiangyang Xue:
Progressive Coordinate Transforms for Monocular 3D Object Detection. 13364-13377 - Bailin Wang, Mirella Lapata, Ivan Titov:
Structured Reordering for Modeling Latent Alignments in Sequence Transduction. 13378-13391 - David Liu, Máté Lengyel:
A universal probabilistic spike count model reveals ongoing modulation of neural variability. 13392-13405 - Chi Jin, Qinghua Liu, Sobhan Miryoosefi:
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms. 13406-13418 - Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann:
Detecting Anomalous Event Sequences with Temporal Point Processes. 13419-13431 - Pedro Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort:
HNPE: Leveraging Global Parameters for Neural Posterior Estimation. 13432-13443 - Shujian Zhang, Xinjie Fan, Huangjie Zheng, Korawat Tanwisuth, Mingyuan Zhou:
Alignment Attention by Matching Key and Query Distributions. 13444-13457 - Jakub Grudzien Kuba, Muning Wen, Linghui Meng, Shangding Gu, Haifeng Zhang, David Mguni, Jun Wang, Yaodong Yang:
Settling the Variance of Multi-Agent Policy Gradients. 13458-13470 - Brian L. Trippe, Hilary K. Finucane, Tamara Broderick:
For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets. 13471-13484 - Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan:
Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations. 13485-13496 - Weili Nie, Arash Vahdat, Anima Anandkumar:
Controllable and Compositional Generation with Latent-Space Energy-Based Models. 13497-13510 - Vincent Mallet, Jean-Philippe Vert:
Reverse-Complement Equivariant Networks for DNA Sequences. 13511-13523 - Tianhao Wang, Dongruo Zhou, Quanquan Gu:
Provably Efficient Reinforcement Learning with Linear Function Approximation under Adaptivity Constraints. 13524-13536 - Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls:
Nonsmooth Implicit Differentiation for Machine-Learning and Optimization. 13537-13549 - Ching-An Cheng, Andrey Kolobov, Adith Swaminathan:
Heuristic-Guided Reinforcement Learning. 13550-13563 - Konstantin Genin:
Statistical Undecidability in Linear, Non-Gaussian Causal Models in the Presence of Latent Confounders. 13564-13574 - Elsa Cazelles, Felipe A. Tobar, Joaquín Fontbona:
A novel notion of barycenter for probability distributions based on optimal weak mass transport. 13575-13586 - Zilin Gao, Qilong Wang, Bingbing Zhang, Qinghua Hu, Peihua Li:
Temporal-attentive Covariance Pooling Networks for Video Recognition. 13587-13598 - Lijun Zhang, Wei Jiang, Shiyin Lu, Tianbao Yang:
Revisiting Smoothed Online Learning. 13599-13612 - Fergus Simpson, Vidhi Lalchand, Carl Edward Rasmussen:
Marginalised Gaussian Processes with Nested Sampling. 13613-13625 - Andrea Zanette, Martin J. Wainwright, Emma Brunskill:
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning. 13626-13640 - Mattie Fellows, Kristian Hartikainen, Shimon Whiteson:
Bayesian Bellman Operators. 13641-13656 - Ruibin Xiong, Yimeng Chen, Liang Pang, Xueqi Cheng, Zhi-Ming Ma, Yanyan Lan:
Uncertainty Calibration for Ensemble-Based Debiasing Methods. 13657-13669 - Junjie Yang, Kaiyi Ji, Yingbin Liang:
Provably Faster Algorithms for Bilevel Optimization. 13670-13682 - Seongjun Yun, Seoyoon Kim, Junhyun Lee, Jaewoo Kang, Hyunwoo J. Kim:
Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction. 13683-13694 - Favyen Bastani, Songtao He, Samuel Madden
Self-Supervised Multi-Object Tracking with Cross-input Consistency. 13695-13706 - Bingzhao Zhu, Mahsa Shoaran:
Tree in Tree: from Decision Trees to Decision Graphs. 13707-13718 - Celestine Mendler-Dünner, Wenshuo Guo, Stephen Bates, Michael I. Jordan:
Test-time Collective Prediction. 13719-13731 - Keyu Tian, Chen Lin, Ser-Nam Lim, Wanli Ouyang, Puneet K. Dokania, Philip H. S. Torr:
A Continuous Mapping For Augmentation Design. 13732-13743 - Kaipeng Zhang, Zhenqiang Li, Zhifeng Li, Wei Liu, Yoichi Sato:
Neural Routing by Memory. 13744-13756 - Octavian Ganea, Lagnajit Pattanaik, Connor W. Coley, Regina Barzilay, Klavs F. Jensen, William H. Green Jr., Tommi S. Jaakkola:
GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles. 13757-13769 - Zhize Li, Peter Richtárik:
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression. 13770-13781 - Nikita Dvornik, Isma Hadji, Konstantinos G. Derpanis, Animesh Garg, Allan D. Jepson:
Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers. 13782-13793 - Tsung-Yen Yang, Michael Y. Hu, Yinlam Chow, Peter J. Ramadge, Karthik Narasimhan:
Safe Reinforcement Learning with Natural Language Constraints. 13794-13808 - Thomas M. McDonald, Mauricio A. Álvarez:
Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features. 13809-13819 - Wenxiao Xiao, Zhengming Ding, Hongfu Liu:
Implicit Semantic Response Alignment for Partial Domain Adaptation. 13820-13833 - Guoqiang Wei, Cuiling Lan, Wenjun Zeng, Zhizheng Zhang, Zhibo Chen:
ToAlign: Task-Oriented Alignment for Unsupervised Domain Adaptation. 13834-13846 - Yuan Deng, Hanrui Zhang:
Prior-independent Dynamic Auctions for a Value-maximizing Buyer. 13847-13858 - Garrett Thomas, Yuping Luo, Tengyu Ma:
Safe Reinforcement Learning by Imagining the Near Future. 13859-13869 - Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Contrastive Active Inference. 13870-13882 - Nilesh Tripuraneni, Ben Adlam, Jeffrey Pennington:
Overparameterization Improves Robustness to Covariate Shift in High Dimensions. 13883-13897 - Jianyu Xu, Yu-Xiang Wang:
Logarithmic Regret in Feature-based Dynamic Pricing. 13898-13910 - Doron Cohen, Aryeh Kontorovich, Aaron Koolyk, Geoffrey Wolfer:
Dimension-free empirical entropy estimation. 13911-13923 - Roman Pogodin, Yash Mehta, Timothy P. Lillicrap, Peter E. Latham:
Towards Biologically Plausible Convolutional Networks. 13924-13936 - Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, Cho-Jui Hsieh:
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification. 13937-13949 - Krishna Kanth Nakka, Mathieu Salzmann:
Learning Transferable Adversarial Perturbations. 13950-13962 - Yi Ren, Jinglin Liu, Zhou Zhao:
PortaSpeech: Portable and High-Quality Generative Text-to-Speech. 13963-13974 - Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Pan Pan, Wotao Yin:
Exponential Graph is Provably Efficient for Decentralized Deep Training. 13975-13987 - Medhini Narasimhan, Anna Rohrbach, Trevor Darrell:
CLIP-It! Language-Guided Video Summarization. 13988-14000 - Vivek F. Farias, Andrew A. Li, Tianyi Peng:
Learning Treatment Effects in Panels with General Intervention Patterns. 14001-14013 - Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison:
Lossy Compression for Lossless Prediction. 14014-14028 - Dorian Baudry, Patrick Saux, Odalric-Ambrym Maillard:
From Optimality to Robustness: Adaptive Re-Sampling Strategies in Stochastic Bandits. 14029-14041 - Guillaume Le Moing, Jean Ponce, Cordelia Schmid:
CCVS: Context-aware Controllable Video Synthesis. 14042-14055 - Zihang Meng, Rudrasis Chakraborty, Vikas Singh:
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis. 14056-14068 - Bhavin Choksi, Milad Mozafari, Callum Biggs O'May, Benjamin Ador, Andrea Alamia, Rufin VanRullen:
Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics. 14069-14083 - Alvin Chan, Ali Madani, Ben Krause, Nikhil Naik:
Deep Extrapolation for Attribute-Enhanced Generation. 14084-14096 - Can Chen, Shuhao Zheng, Xi Chen, Erqun Dong, Xue (Steve) Liu, Hao Liu, Dejing Dou:
Generalized DataWeighting via Class-Level Gradient Manipulation. 14097-14109 - Can Qin, Handong Zhao, Lichen Wang, Huan Wang, Yulun Zhang, Yun Fu:
Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation. 14110-14121 - Louis Kirsch, Jürgen Schmidhuber:
Meta Learning Backpropagation And Improving It. 14122-14134 - Christian Henning, Maria R. Cervera, Francesco D'Angelo, Johannes von Oswald, Regina Traber, Benjamin Ehret, Seijin Kobayashi, Benjamin F. Grewe, João Sacramento:
Posterior Meta-Replay for Continual Learning. 14135-14149 - Julio Hurtado, Alain Raymond-Saez, Alvaro Soto:
Optimizing Reusable Knowledge for Continual Learning via Metalearning. 14150-14162 - Camille E. Rullán Buxó, Cristina Savin:
A sampling-based circuit for optimal decision making. 14163-14175 - Yuqi Huo, Mingyu Ding, Haoyu Lu, Nanyi Fei, Zhiwu Lu, Ji-Rong Wen, Ping Luo:
Compressed Video Contrastive Learning. 14176-14187 - Jiafan He, Dongruo Zhou, Quanquan Gu:
Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation. 14188-14199 - Arsha Nagrani, Shan Yang, Anurag Arnab, Aren Jansen, Cordelia Schmid, Chen Sun:
Attention Bottlenecks for Multimodal Fusion. 14200-14213 - Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher
Convergence of adaptive algorithms for constrained weakly convex optimization. 14214-14225 - Xiaoyu Wang, Sindri Magnússon, Mikael Johansson:
On the Convergence of Step Decay Step-Size for Stochastic Optimization. 14226-14238 - Mingguo He, Zhewei Wei, Zengfeng Huang
BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation. 14239-14251 - He Zhang, Fusong Ju, Jianwei Zhu, Liang He, Bin Shao, Nanning Zheng, Tie-Yan Liu:
Co-evolution Transformer for Protein Contact Prediction. 14252-14263 - Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu:
Unsupervised Foreground Extraction via Deep Region Competition. 14264-14279 - Divyansh Jhunjhunwala, Ankur Mallick, Advait Gadhikar, Swanand Kadhe, Gauri Joshi:
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation. 14280-14292 - Chung-Wei Lee, Christian Kroer, Haipeng Luo:
Last-iterate Convergence in Extensive-Form Games. 14293-14305 - Fei Zhu, Zhen Cheng, Xu-Yao Zhang, Cheng-Lin Liu:
Class-Incremental Learning via Dual Augmentation. 14306-14318 - Zixiu Wang, Yiwen Guo, Hu Ding:
Robust and Fully-Dynamic Coreset for Continuous-and-Bounded Learning (With Outliers) Problems. 14319-14331 - Guoqiang Wu, Chongxuan Li, Kun Xu, Jun Zhu:
Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization. 14332-14344 - Seyed A. Esmaeili, Brian Brubach, Aravind Srinivasan, John Dickerson:
Fair Clustering Under a Bounded Cost. 14345-14357 - Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi:
Improving Calibration through the Relationship with Adversarial Robustness. 14358-14369 - Julian Lienen, Eyke Hüllermeier:
Credal Self-Supervised Learning. 14370-14382 - Steffen Czolbe, Aasa Feragen, Oswin Krause:
Spot the Difference: Detection of Topological Changes via Geometric Alignment. 14383-14395 - Peiyuan Zhang, Antonio Orvieto, Hadi Daneshmand:
Rethinking the Variational Interpretation of Accelerated Optimization Methods. 14396-14406 - Arvind V. Mahankali, David P. Woodruff:
Linear and Kernel Classification in the Streaming Model: Improved Bounds for Heavy Hitters. 14407-14420 - Paul Viallard, Guillaume Vidot, Amaury Habrard, Emilie Morvant:
A PAC-Bayes Analysis of Adversarial Robustness. 14421-14433 - Oliver T. Unke, Mihail Bogojeski, Michael Gastegger, Mario Geiger, Tess E. Smidt
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities. 14434-14447 - Carson Kent, Jiajin Li, José H. Blanchet, Peter W. Glynn:
Modified Frank Wolfe in Probability Space. 14448-14462 - Raul Astudillo, Peter I. Frazier:
Bayesian Optimization of Function Networks. 14463-14475 - Reuben Tan, Bryan A. Plummer, Kate Saenko, Hailin Jin, Bryan Russell:
Look at What I'm Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos. 14476-14487 - KrishnaTeja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer:
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. 14488-14501 - DJ Strouse, Kevin R. McKee, Matt M. Botvinick, Edward Hughes, Richard Everett:
Collaborating with Humans without Human Data. 14502-14515 - Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin:
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State. 14516-14528 - Aditya Gangrade, Anil Kag, Ashok Cutkosky
Online Selective Classification with Limited Feedback. 14529-14541 - Sachin Kumar, Eric Malmi, Aliaksei Severyn, Yulia Tsvetkov:
Controlled Text Generation as Continuous Optimization with Multiple Constraints. 14542-14554 - Xinlin Li, Bang Liu, Yaoliang Yu, Wulong Liu, Chunjing Xu, Vahid Partovi Nia:
S$^3$: Sign-Sparse-Shift Reparametrization for Effective Training of Low-bit Shift Networks. 14555-14566 - Mathias Niepert, Pasquale Minervini, Luca Franceschi:
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions. 14567-14579 - Alkis Gotovos, Rebekka Burkholz, John Quackenbush, Stefanie Jegelka:
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification. 14580-14592 - Alexander Korotin, Lingxiao Li, Aude Genevay, Justin M. Solomon, Alexander Filippov, Evgeny Burnaev:
Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark. 14593-14605 - Aritra Mitra, Rayana H. Jaafar, George J. Pappas, Hamed Hassani:
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients. 14606-14619 - Shuyu Cheng, Guoqiang Wu, Jun Zhu:
On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms. 14620-14631 - Milad Abdollahzadeh, Touba Malekzadeh, Ngai-Man Cheung:
Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning. 14632-14644 - Hiroaki Yamada, Makoto Yamada:
Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares. 14645-14655 - Manu Orsini, Anton Raichuk, Léonard Hussenot, Damien Vincent, Robert Dadashi, Sertan Girgin, Matthieu Geist, Olivier Bachem, Olivier Pietquin, Marcin Andrychowicz:
What Matters for Adversarial Imitation Learning? 14656-14668 - Daniel Kumor, Junzhe Zhang, Elias Bareinboim:
Sequential Causal Imitation Learning with Unobserved Confounders. 14669-14680 - Dazhong Shen, Chuan Qin, Chao Wang, Zheng Dong, Hengshu Zhu, Hui Xiong:
Topic Modeling Revisited: A Document Graph-based Neural Network Perspective. 14681-14693 - Athanasios Papadopoulos, Pawel Korus, Nasir D. Memon:
Hard-Attention for Scalable Image Classification. 14694-14707 - Dong Quan Vu, Kimon Antonakopoulos, Panayotis Mertikopoulos:
Fast Routing under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights. 14708-14720 - Xingchao Liu, Xin Tong, Qiang Liu:
Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent. 14721-14733 - Stephen Chung:
MAP Propagation Algorithm: Faster Learning with a Team of Reinforcement Learning Agents. 14734-14744 - Yifan Jiang, Shiyu Chang, Zhangyang Wang:
TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up. 14745-14758 - Jinshuo Dong, Weijie J. Su, Linjun Zhang:
A Central Limit Theorem for Differentially Private Query Answering. 14759-14770 - Rishav Chourasia, Jiayuan Ye, Reza Shokri:
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent. 14771-14781 - Maria-Florina Balcan, Dravyansh Sharma:
Data driven semi-supervised learning. 14782-14794 - Sudarshan Babu, Pedro Savarese, Michael Maire:
Meta-Learning via Learning with Distributed Memory. 14795-14808 - Naoya Takeishi, Alexandros Kalousis
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling. 14809-14821 - Ulrich Aïvodji, Hiromi Arai, Sébastien Gambs, Satoshi Hara:
Characterizing the risk of fairwashing. 14822-14834 - Kanghyun Choi, Deokki Hong, Noseong Park, Youngsok Kim, Jinho Lee:
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples. 14835-14847 - Yaoyu Zhang, Zhongwang Zhang, Tao Luo, Zhi-Qin John Xu:
Embedding Principle of Loss Landscape of Deep Neural Networks. 14848-14859 - Xiang Gu, Xi Yu, Yan Yang, Jian Sun, Zongben Xu:
Adversarial Reweighting for Partial Domain Adaptation. 14860-14872 - Elias Frantar, Eldar Kurtic, Dan Alistarh:
M-FAC: Efficient Matrix-Free Approximations of Second-Order Information. 14873-14886 - Longqi Yang, Liangliang Zhang, Wenjing Yang:
Graph Adversarial Self-Supervised Learning. 14887-14899 - Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma:
Anti-Backdoor Learning: Training Clean Models on Poisoned Data. 14900-14912 - Keunseo Kim, Juncheol Shin, Heeyoung Kim:
Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models. 14913-14924 - Qiyu Kang, Yang Song, Qinxu Ding, Wee Peng Tay:
Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks. 14925-14937 - Ajil Jalal, Marius Arvinte, Giannis Daras, Eric Price, Alexandros G. Dimakis, Jonathan I. Tamir:
Robust Compressed Sensing MRI with Deep Generative Priors. 14938-14954 - Hongyi Xu, Thiemo Alldieck, Cristian Sminchisescu:
H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motion. 14955-14966 - Marie-Anne Lachaux, Baptiste Rozière, Marc Szafraniec, Guillaume Lample:
DOBF: A Deobfuscation Pre-Training Objective for Programming Languages. 14967-14979 - Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha:
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles. 14980-14992 - Huangjie Zheng, Mingyuan Zhou:
Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions. 14993-15006 - Tian-Zuo Wang, Zhi-Hua Zhou:
Actively Identifying Causal Effects with Latent Variables Given Only Response Variable Observable. 15007-15018 - Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting:
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. 15019-15031 - Justin K. Terry, Benjamin Black, Nathaniel Grammel, Mario Jayakumar, Ananth Hari, Ryan Sullivan, Luis S. Santos, Clemens Dieffendahl, Caroline Horsch, Rodrigo Perez-Vicente, Niall L. Williams, Yashas Lokesh, Praveen Ravi:
PettingZoo: Gym for Multi-Agent Reinforcement Learning. 15032-15043 - Tanya Marwah, Zachary C. Lipton, Andrej Risteski:
Parametric Complexity Bounds for Approximating PDEs with Neural Networks. 15044-15055 - Maria-Florina Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar:
Learning-to-learn non-convex piecewise-Lipschitz functions. 15056-15069 - Cassidy Laidlaw, Stuart Russell:
Uncertain Decisions Facilitate Better Preference Learning. 15070-15083 - Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch:
Decision Transformer: Reinforcement Learning via Sequence Modeling. 15084-15097 - Zhiyuan (Jerry) Lin, Hao Sheng, Sharad Goel:
Probability Paths and the Structure of Predictions over Time. 15098-15110 - Qixian Zhong, Jonas Mueller, Jane-Ling Wang:
Deep Extended Hazard Models for Survival Analysis. 15111-15124 - Shun Lu, Jixiang Li, Jianchao Tan, Sen Yang, Ji Liu:
TNASP: A Transformer-based NAS Predictor with a Self-evolution Framework. 15125-15137 - Fengli Xu, Quanming Yao, Pan Hui, Yong Li:
Automorphic Equivalence-aware Graph Neural Network. 15138-15150 - Itay Safran, Ohad Shamir:
Random Shuffling Beats SGD Only After Many Epochs on Ill-Conditioned Problems. 15151-15161 - Yossi Arjevani, Michael Field:
Analytic Study of Families of Spurious Minima in Two-Layer ReLU Neural Networks: A Tale of Symmetry II. 15162-15174 - Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai:
CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks. 15175-15187 - Son Nguyen, Duong Nguyen, Khai Nguyen, Khoat Than, Hung Bui, Nhat Ho:
Structured Dropout Variational Inference for Bayesian Neural Networks. 15188-15202 - Quan Zheng, Gurprit Singh, Hans-Peter Seidel:
Neural Relightable Participating Media Rendering. 15203-15215 - Xiao Zhou, Weizhong Zhang, Zonghao Chen, Shizhe Diao, Tong Zhang:
Efficient Neural Network Training via Forward and Backward Propagation Sparsification. 15216-15229 - Toru Lin, Jacob Huh, Christopher Stauffer, Ser-Nam Lim, Phillip Isola:
Learning to Ground Multi-Agent Communication with Autoencoders. 15230-15242 - Petr Mokrov, Alexander Korotin, Lingxiao Li, Aude Genevay, Justin M. Solomon, Evgeny Burnaev:
Large-Scale Wasserstein Gradient Flows. 15243-15256 - Tijana Zrnic, Eric Mazumdar, S. Shankar Sastry, Michael I. Jordan:
Who Leads and Who Follows in Strategic Classification? 15257-15269 - Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor:
Unadversarial Examples: Designing Objects for Robust Vision. 15270-15284 - Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu:
Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings. 15285-15300 - Trenton Bricken, Cengiz Pehlevan:
Attention Approximates Sparse Distributed Memory. 15301-15315 - Yehui Tang, Kai Han, Chang Xu, An Xiao, Yiping Deng, Chao Xu, Yunhe Wang:
Augmented Shortcuts for Vision Transformers. 15316-15327 - Justin Lim, Christina X. Ji, Michael Oberst, Saul Blecker, Leora Horwitz, David A. Sontag:
Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance. 15328-15343 - David Madras, Richard S. Zemel:
Identifying and Benchmarking Natural Out-of-Context Prediction Problems. 15344-15358 - Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon:
Label Disentanglement in Partition-based Extreme Multilabel Classification. 15359-15369 - Xiaolong Li, Yijia Weng, Li Yi, Leonidas J. Guibas, A. Lynn Abbott, Shuran Song, He Wang:
Leveraging SE(3) Equivariance for Self-supervised Category-Level Object Pose Estimation from Point Clouds. 15370-15381 - Gal Shachaf, Alon Brutzkus, Amir Globerson:
A Theoretical Analysis of Fine-tuning with Linear Teachers. 15382-15394 - Brandon Carter, Siddhartha Jain, Jonas Mueller, David Gifford:
Overinterpretation reveals image classification model pathologies. 15395-15407 - Frederik Schmitt, Christopher Hahn, Markus N. Rabe, Bernd Finkbeiner:
Neural Circuit Synthesis from Specification Patterns. 15408-15420 - Johannes Gasteiger, Chandan Yeshwanth, Stephan Günnemann:
Directional Message Passing on Molecular Graphs via Synthetic Coordinates. 15421-15433 - Othmane Marfoq, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, Richard Vidal:
Federated Multi-Task Learning under a Mixture of Distributions. 15434-15447 - Jing Zhang, Jianwen Xie, Nick Barnes, Ping Li:
Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction. 15448-15463 - Soufiane Hayou, Fadhel Ayed:
Regularization in ResNet with Stochastic Depth. 15464-15474 - Qinglong Zhang, Yu-Bin Yang:
ResT: An Efficient Transformer for Visual Recognition. 15475-15485 - Chawin Sitawarin, Evgenios M. Kornaropoulos, Dawn Song, David A. Wagner:
Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams. 15486-15497 - Jiachen Sun, Yulong Cao, Christopher B. Choy, Zhiding Yu, Anima Anandkumar, Zhuoqing Morley Mao, Chaowei Xiao:
Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions. 15498-15512 - Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts:
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. 15513-15528 - Andreea Deac, Petar Velickovic, Ognjen Milinkovic, Pierre-Luc Bacon, Jian Tang, Mladen Nikolic:
Neural Algorithmic Reasoners are Implicit Planners. 15529-15542 - Yazhe Li, Roman Pogodin, Danica J. Sutherland, Arthur Gretton:
Self-Supervised Learning with Kernel Dependence Maximization. 15543-15556 - Dani Kiyasseh, Tingting Zhu, David A. Clifton:
CROCS: Clustering and Retrieval of Cardiac Signals Based on Patient Disease Class, Sex, and Age. 15557-15569 - Tao Yu, Christopher De Sa:
Representing Hyperbolic Space Accurately using Multi-Component Floats. 15570-15581 - Zachary Izzo, Sandeep Silwal, Samson Zhou:
Dimensionality Reduction for Wasserstein Barycenter. 15582-15594 - Joel Dapello, Jenelle Feather, Hang Le, Tiago Marques, David D. Cox, Josh H. McDermott, James J. DiCarlo, SueYeon Chung:
Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception. 15595-15607 - Yilun Du, Shuang Li, Yash Sharma, Josh Tenenbaum, Igor Mordatch:
Unsupervised Learning of Compositional Energy Concepts. 15608-15620 - Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi:
Nearly Horizon-Free Offline Reinforcement Learning. 15621-15634 - Ahmed Abbas, Paul Swoboda:
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach. 15635-15649 - Hyunji Alex Nam, Scott L. Fleming, Emma Brunskill:
Reinforcement Learning with State Observation Costs in Action-Contingent Noiselessly Observable Markov Decision Processes. 15650-15666 - Joseph Marino, Alexandre Piché, Alessandro Davide Ialongo, Yisong Yue:
Iterative Amortized Policy Optimization. 15667-15681 - Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic:
Revisiting the Calibration of Modern Neural Networks. 15682-15694 - Yu-Chia Chen, Marina Meila:
The decomposition of the higher-order homology embedding constructed from the $k$-Laplacian. 15695-15709 - Han Zhong, Jiayi Huang, Lin Yang
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs. 15710-15720 - Lizhen Nie, Dan Nicolae:
A nonparametric method for gradual change problems with statistical guarantees. 15721-15733 - Muhan Zhang, Pan Li:
Nested Graph Neural Networks. 15734-15747 - Paul-Ambroise Duquenne, Hongyu Gong, Holger Schwenk:
Multimodal and Multilingual Embeddings for Large-Scale Speech Mining. 15748-15761 - Jakob Runge:
Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables. 15762-15773 - Stelios Triantafyllou, Adish Singla, Goran Radanovic:
On Blame Attribution for Accountable Multi-Agent Sequential Decision Making. 15774-15786 - Jonathan Bragg, Arman Cohan
FLEX: Unifying Evaluation for Few-Shot NLP. 15787-15800 - Mohammad Bashiri, Edgar Y. Walker, Konstantin-Klemens Lurz, Akshay Kumar Jagadish, Taliah Muhammad, Zhiwei Ding, Zhuokun Ding, Andreas S. Tolias, Fabian H. Sinz:
A flow-based latent state generative model of neural population responses to natural images. 15801-15815 - Yang Li, Si Si, Gang Li, Cho-Jui Hsieh, Samy Bengio:
Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding. 15816-15829 - Wonyoung Kim, Gi-Soo Kim, Myunghee Cho Paik:
Doubly Robust Thompson Sampling with Linear Payoffs. 15830-15840 - Abhin Shah, Devavrat Shah, Gregory W. Wornell:
A Computationally Efficient Method for Learning Exponential Family Distributions. 15841-15854 - Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar:
Rethinking Neural Operations for Diverse Tasks. 15855-15869 - Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Chee-Kong Lee:
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction. 15870-15882 - Alicia Curth, Mihaela van der Schaar:
On Inductive Biases for Heterogeneous Treatment Effect Estimation. 15883-15894 - Yi Xu, Jiandong Ding, Lu Zhang, Shuigeng Zhou:
DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples. 15895-15907 - Kai Han, An Xiao, Enhua Wu, Jianyuan Guo, Chunjing Xu, Yunhe Wang:
Transformer in Transformer. 15908-15919 - Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville:
Adversarial Graph Augmentation to Improve Graph Contrastive Learning. 15920-15933 - Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan:
Online Control of Unknown Time-Varying Dynamical Systems. 15934-15945 - Gabriel Poesia, Wenxin Dong, Noah D. Goodman:
Contrastive Reinforcement Learning of Symbolic Reasoning Domains. 15946-15956 - Tengteng Huang, Yifan Sun, Xun Wang, Haotian Yao, Chi Zhang:
Spatial Ensemble: a Novel Model Smoothing Mechanism for Student-Teacher Framework. 15957-15968 - Hugo Soulat, Sepiedeh Keshavarzi, Troy W. Margrie, Maneesh Sahani:
Probabilistic Tensor Decomposition of Neural Population Spiking Activity. 15969-15980 - Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Emmanuel Agu, Elke A. Rundensteiner:
Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification. 15981-15992 - Yufeng Zhang, Siyu Chen, Zhuoran Yang, Michael I. Jordan, Zhaoran Wang:
Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic. 15993-16006 - Yiliang Zhang, Qi Long:
Assessing Fairness in the Presence of Missing Data. 16007-16019 - Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li:
Adversarial Attack Generation Empowered by Min-Max Optimization. 16020-16033 - Wanxin Jin, Shaoshuai Mou, George J. Pappas:
Safe Pontryagin Differentiable Programming. 16034-16050 - Kaiwen Yang, Tianyi Zhou, Yonggang Zhang, Xinmei Tian, Dacheng Tao:
Class-Disentanglement and Applications in Adversarial Detection and Defense. 16051-16063 - Edward J. Smith, David Meger, Luis Pineda, Roberto Calandra, Jitendra Malik, Adriana Romero-Soriano, Michal Drozdzal:
Active 3D Shape Reconstruction from Vision and Touch. 16064-16078 - Tatiana Likhomanenko, Qiantong Xu, Gabriel Synnaeve, Ronan Collobert, Alex Rogozhnikov:
CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings. 16079-16092 - Ningyuan Chen:
Multi-armed Bandit Requiring Monotone Arm Sequences. 16093-16103 - Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, Bryan Kian Hsiang Low:
Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning. 16104-16117 - Youngwoon Lee, Andrew Szot, Shao-Hua Sun, Joseph J. Lim:
Generalizable Imitation Learning from Observation via Inferring Goal Proximity. 16118-16130 - Quang Pham, Chenghao Liu, Steven C. H. Hoi:
DualNet: Continual Learning, Fast and Slow. 16131-16144 - Rui Lin, Jie Ran, King Hung Chiu, Graziano Chesi, Ngai Wong:
Deformable Butterfly: A Highly Structured and Sparse Linear Transform. 16145-16157 - Colin Wei, Sang Michael Xie, Tengyu Ma:
Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning. 16158-16170 - Yiming Gao, Bei Shi, Xueying Du, Liang Wang, Guangwei Chen, Zhenjie Lian, Fuhao Qiu, Guoan Han, Weixuan Wang, Deheng Ye, Qiang Fu, Wei Yang, Lanxiao Huang:
Learning Diverse Policies in MOBA Games via Macro-Goals. 16171-16182 - Ho Chit Siu, Jaime Daniel Peña, Edenna Chen, Yutai Zhou, Victor J. Lopez, Kyle Palko, Kimberlee C. Chang, Ross E. Allen:
Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi. 16183-16195 - Victor Veitch, Alexander D'Amour, Steve Yadlowsky, Jacob Eisenstein:
Counterfactual Invariance to Spurious Correlations in Text Classification. 16196-16208 - Lue Tao, Lei Feng, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen:
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training. 16209-16225 - Rémi Bardenet, Subhroshekhar Ghosh, Meixia Lin:
Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD. 16226-16237 - Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Luc Van Gool:
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. 16238-16250 - Hyeong-Seok Choi, Juheon Lee, Wansoo Kim, Jie Lee, Hoon Heo, Kyogu Lee:
Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations. 16251-16265 - Fenglin Liu, Chenyu You, Xian Wu, Shen Ge, Sheng Wang, Xu Sun:
Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation. 16266-16279 - Qinsheng Zhang, Yongxin Chen:
Diffusion Normalizing Flow. 16280-16291 - Yulei Niu, Hanwang Zhang:
Introspective Distillation for Robust Question Answering. 16292-16304 - Zhongzhan Huang, Wenqi Shao, Xinjiang Wang, Liang Lin, Ping Luo:
Rethinking the Pruning Criteria for Convolutional Neural Network. 16305-16318 - Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Chris Waites:
Adaptive Machine Unlearning. 16319-16330 - Huan Ling, Karsten Kreis, Daiqing Li, Seung Wook Kim, Antonio Torralba, Sanja Fidler:
EditGAN: High-Precision Semantic Image Editing. 16331-16345 - Shuwen Yang, Ziyao Li, Guojie Song, Lingsheng Cai:
Deep Molecular Representation Learning via Fusing Physical and Chemical Information. 16346-16357 - Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii:
Neural optimal feedback control with local learning rules. 16358-16370 - Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta:
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection. 16371-16383 - Ferran Alet, Dylan Doblar, Allan Zhou, Josh Tenenbaum, Kenji Kawaguchi, Chelsea Finn:
Noether Networks: meta-learning useful conserved quantities. 16384-16397 - Qian Ning, Weisheng Dong, Xin Li, Jinjian Wu, Guangming Shi:
Uncertainty-Driven Loss for Single Image Super-Resolution. 16398-16409 - Chen Zhu, Renkun Ni, Zheng Xu, Kezhi Kong, W. Ronny Huang, Tom Goldstein:
GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training. 16410-16422 - Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L. Clarkson, Andrew McCallum:
Capacity and Bias of Learned Geometric Embeddings for Directed Graphs. 16423-16436 - Mikio Ludwig Braun, Tim P. Vogels:
Online Learning Of Neural Computations From Sparse Temporal Feedback. 16437-16450 - Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello:
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style. 16451-16467 - Zijian Kang, Peizhen Zhang, Xiangyu Zhang, Jian Sun, Nanning Zheng:
Instance-Conditional Knowledge Distillation for Object Detection. 16468-16480 - Konstantin Schürholt, Dimche Kostadinov, Damian Borth:
Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction. 16481-16493 - Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl:
Multimodal Virtual Point 3D Detection. 16494-16507 - Ruoyu Cheng, Junchi Yan:
On Joint Learning for Solving Placement and Routing in Chip Design. 16508-16519 - Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen:
Learning with Algorithmic Supervision via Continuous Relaxations. 16520-16531 - Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama:
Differentiable Multiple Shooting Layers. 16532-16544 - Ye Ma, Zixun Lan, Lu Zong, Kaizhu Huang:
Global-aware Beam Search for Neural Abstractive Summarization. 16545-16557 - Zachary Teed, Jia Deng:
DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras. 16558-16569 - Yuhang Cao, Jiaqi Wang, Ying Jin, Tong Wu, Kai Chen, Ziwei Liu, Dahua Lin:
Few-Shot Object Detection via Association and DIscrimination. 16570-16581 - Chenxu Hu, Qiao Tian, Tingle Li, Yuping Wang, Yuxuan Wang, Hang Zhao:
Neural Dubber: Dubbing for Videos According to Scripts. 16582-16595 - Minsuk Shin, Hyungjoo Cho, Hyun-seok Min, Sungbin Lim:
Neural Bootstrapper. 16596-16609 - Cyrus Cousins:
An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning. 16610-16621 - Shiming Chen, Guo-Sen Xie, Yang Liu, Qinmu Peng, Baigui Sun, Hao Li, Xinge You, Ling Shao:
HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning. 16622-16634 - Cristopher Salvi, Maud Lemercier, Chong Liu, Blanka Horvath, Theodoros Damoulas, Terry J. Lyons:
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes. 16635-16647 - Jiapeng Zhu, Ruili Feng, Yujun Shen, Deli Zhao, Zheng-Jun Zha, Jingren Zhou, Qifeng Chen:
Low-Rank Subspaces in GANs. 16648-16658 - Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi:
Neural Symplectic Form: Learning Hamiltonian Equations on General Coordinate Systems. 16659-16670 - Gen Li, Yuxin Chen, Yuejie Chi, Yuantao Gu, Yuting Wei:
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting. 16671-16685 - Jizong Peng, Ping Wang, Christian Desrosiers, Marco Pedersoli:
Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels. 16686-16699 - Jimmy T. H. Smith, Scott W. Linderman, David Sussillo:
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems. 16700-16713 - Antonios Antoniadis, Christian Coester, Marek Eliás, Adam Polak, Bertrand Simon:
Learning-Augmented Dynamic Power Management with Multiple States via New Ski Rental Bounds. 16714-16726 - Priyank Jaini, Lars Holdijk, Max Welling:
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent. 16727-16737 - Botao Hao, Tor Lattimore, Wei Deng:
Information Directed Sampling for Sparse Linear Bandits. 16738-16750 - Xiao Lv, Wei Cui, Yulong Liu:
Linear Convergence of Gradient Methods for Estimating Structured Transition Matrices in High-dimensional Vector Autoregressive Models. 16751-16763 - Huy V. Vo, Elena Sizikova, Cordelia Schmid, Patrick Pérez, Jean Ponce:
Large-Scale Unsupervised Object Discovery. 16764-16778 - Jiehong Lin, Hongyang Li, Ke Chen, Jiangbo Lu, Kui Jia:
Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space. 16779-16790 - Xingsi Dong, Tianhao Chu, Tiejun Huang, Zilong Ji, Si Wu:
Noisy Adaptation Generates Lévy Flights in Attractor Neural Networks. 16791-16804 - Chao Ma, Lexing Ying:
On Linear Stability of SGD and Input-Smoothness of Neural Networks. 16805-16817 - Swaminathan Gurumurthy, Shaojie Bai, Zachary Manchester, J. Zico Kolter:
Joint inference and input optimization in equilibrium networks. 16818-16832 - Ziyu Xu, Ruodu Wang, Aaditya Ramdas:
A unified framework for bandit multiple testing. 16833-16845 - Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu:
Recovering Latent Causal Factor for Generalization to Distributional Shifts. 16846-16859 - Yijian Qin, Xin Wang, Zeyang Zhang, Wenwu Zhu:
Graph Differentiable Architecture Search with Structure Learning. 16860-16872 - Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jia Liang, Akshay Chaudhari, Andreas Spanias:
Designing Counterfactual Generators using Deep Model Inversion. 16873-16884 - Nathaniel Lahn, Sharath Raghvendra, Jiacheng Ye:
A Faster Maximum Cardinality Matching Algorithm with Applications in Machine Learning. 16885-16898 - Abhinav Gupta, Marc Lanctot, Angeliki Lazaridou:
Dynamic population-based meta-learning for multi-agent communication with natural language. 16899-16912 - Dongxian Wu, Yisen Wang:
Adversarial Neuron Pruning Purifies Backdoored Deep Models. 16913-16925 - Sohini Upadhyay, Shalmali Joshi, Himabindu Lakkaraju:
Towards Robust and Reliable Algorithmic Recourse. 16926-16937 - Yufei Wang, Can Xu, Huang Hu, Chongyang Tao, Stephen Wan, Mark Dras, Mark Johnson, Daxin Jiang:
Neural Rule-Execution Tracking Machine For Transformer-Based Text Generation. 16938-16950 - Arnaud Fickinger, Hengyuan Hu, Brandon Amos, Stuart J. Russell, Noam Brown:
Scalable Online Planning via Reinforcement Learning Fine-Tuning. 16951-16963 - Tam Le, Truyen Nguyen, Makoto Yamada, Jose H. Blanchet, Viet Anh Nguyen:
Adversarial Regression with Doubly Non-negative Weighting Matrices. 16964-16976 - HanQin Cai, Jialin Liu, Wotao Yin:
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection. 16977-16989 - Antoine Labatie, Dominic Masters, Zach Eaton-Rosen, Carlo Luschi:
Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence. 16990-17006 - Chenjia Bai, Lingxiao Wang, Lei Han, Animesh Garg, Jianye Hao, Peng Liu, Zhaoran Wang:
Dynamic Bottleneck for Robust Self-Supervised Exploration. 17007-17020 - Zelin Zhao, Karan Samel, Binghong Chen, Le Song:
ProTo: Program-Guided Transformer for Program-Guided Tasks. 17021-17036 - Tianpei Yang, Weixun Wang, Hongyao Tang, Jianye Hao, Zhaopeng Meng, Hangyu Mao, Dong Li, Wulong Liu, Yingfeng Chen, Yujing Hu, Changjie Fan, Chengwei Zhang:
An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning. 17037-17048 - Nicolas Skatchkovsky, Osvaldo Simeone, Hyeryung Jang:
Learning to Time-Decode in Spiking Neural Networks Through the Information Bottleneck. 17049-17059 - Achille Thin, Yazid Janati El Idrissi, Sylvain Le Corff, Charles Ollion, Eric Moulines, Arnaud Doucet, Alain Durmus, Christian X. Robert:
NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform. 17060-17071 - Klas Leino, Matt Fredrikson:
Relaxing Local Robustness. 17072-17083 - Ge Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu, David Farhi, Nick Ryder, Jakub Pachocki, Weizhu Chen, Jianfeng Gao:
Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer. 17084-17097 - Anish Chakrabarty, Swagatam Das:
Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency. 17098-17110 - Christopher Michael Rytting, David Wingate:
Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning. 17111-17122 - Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin:
Differentiable Simulation of Soft Multi-body Systems. 17123-17135 - Martijn Gösgens, Anton Zhiyanov, Aleksey Tikhonov, Liudmila Prokhorenkova:
Good Classification Measures and How to Find Them. 17136-17147 - Junho Kim, Byung-Kwan Lee, Yong Man Ro:
Distilling Robust and Non-Robust Features in Adversarial Examples by Information Bottleneck. 17148-17159 - Michael J. Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth:
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels. 17160-17169 - Christian Bueno, Alan Hylton:
On the Representation Power of Set Pooling Networks. 17170-17182 - Tao Liu, Ruida Zhou, Dileep Kalathil, Panganamala R. Kumar, Chao Tian:
Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs. 17183-17193 - Korawat Tanwisuth, Xinjie Fan, Huangjie Zheng, Shujian Zhang, Hao Zhang, Bo Chen, Mingyuan Zhou:
A Prototype-Oriented Framework for Unsupervised Domain Adaptation. 17194-17208 - Aixi Zhang, Yue Liao, Si Liu, Miao Lu, Yongliang Wang, Chen Gao, Xiaobo Li:
Mining the Benefits of Two-stage and One-stage HOI Detection. 17209-17220 - Ying Sun, Hengshu Zhu, Chuan Qin, Fuzhen Zhuang, Qing He, Hui Xiong:
Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation. 17221-17234 - Anastasia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause:
Risk-averse Heteroscedastic Bayesian Optimization. 17235-17245 - Yura Perugachi-Diaz, Jakub M. Tomczak, Sandjai Bhulai:
Invertible DenseNets with Concatenated LipSwish. 17246-17257 - Songzhu Zheng, Yikai Zhang, Hubert Wagner, Mayank Goswami, Chao Chen:
Topological Detection of Trojaned Neural Networks. 17258-17272 - Bryn Elesedy:
Provably Strict Generalisation Benefit for Invariance in Kernel Methods. 17273-17283 - Krishnan Raghavan, Prasanna Balaprakash:
Formalizing the Generalization-Forgetting Trade-off in Continual Learning. 17284-17297 - Michael Gimelfarb, André Barreto, Scott Sanner, Chi-Guhn Lee:
Risk-Aware Transfer in Reinforcement Learning using Successor Features. 17298-17310 - Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Xiao Shou, Nicholas Mattei, Kristin P. Bennett:
Causal Inference for Event Pairs in Multivariate Point Processes. 17311-17324 - Mike Li, Hongseok Namkoong, Shangzhou Xia:
Evaluating model performance under worst-case subpopulations. 17325-17334 - Rachel Redberg, Yu-Xiang Wang:
Privately Publishable Per-instance Privacy. 17335-17346 - Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm:
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning. 17347-17359 - Vladimir Braverman, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu:
Coresets for Clustering with Missing Values. 17360-17372 - Corinna Cortes, Mehryar Mohri, Dmitry Storcheus, Ananda Theertha Suresh:
Boosting with Multiple Sources. 17373-17387 - Bowen Zhang, Yifan Liu, Zhi Tian, Chunhua Shen:
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation. 17388-17399 - Zhixuan Yu, Haozheng Yu, Long Sha, Sujoy Ganguly, Hyun Soo Park:
Dense Keypoints via Multiview Supervision. 17400-17412 - Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré:
Scatterbrain: Unifying Sparse and Low-rank Attention. 17413-17426 - Yining Hong, Li Yi, Josh Tenenbaum, Antonio Torralba, Chuang Gan:
PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning. 17427-17440 - Yaqing Wang, Abulikemu Abuduweili, Quanming Yao, Dejing Dou:
Property-Aware Relation Networks for Few-Shot Molecular Property Prediction. 17441-17454 - Galen Andrew, Om Thakkar, Brendan McMahan, Swaroop Ramaswamy:
Differentially Private Learning with Adaptive Clipping. 17455-17466 - Yang Liu, Jialu Wang:
Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial. 17467-17479 - Axel Sauer, Kashyap Chitta, Jens Müller, Andreas Geiger:
Projected GANs Converge Faster. 17480-17492 - Gregory J. Stein:
Generating High-Quality Explanations for Navigation in Partially-Revealed Environments. 17493-17506 - Zheyang Shen, Markus Heinonen, Samuel Kaski:
De-randomizing MCMC dynamics with the diffusion Stein operator. 17507-17517 - Christian Gumbsch, Martin V. Butz, Georg Martius:
Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains. 17518-17531 - Neehar Peri, Michael J. Curry, Samuel Dooley, John Dickerson:
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. 17532-17542 - Frederiek Wesel, Kim Batselier:
Large-Scale Learning with Fourier Features and Tensor Decompositions. 17543-17554 - Stephen Roller, Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston:
Hash Layers For Large Sparse Models. 17555-17566 - Ziv Goldfeld, Kristjan H. Greenewald:
Sliced Mutual Information: A Scalable Measure of Statistical Dependence. 17567-17578 - Jooyeon Kim, Alice Oh:
Emergent Communication under Varying Sizes and Connectivities. 17579-17591 - Rong Zhu, Mattia Rigotti:
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks. 17592-17603 - Xu-Hui Liu, Zhenghai Xue, Jing-Cheng Pang, Shengyi Jiang, Feng Xu, Yang Yu:
Regret Minimization Experience Replay in Off-Policy Reinforcement Learning. 17604-17615 - Yuhang Zhang, Chengrui Wang, Weihong Deng:
Relative Uncertainty Learning for Facial Expression Recognition. 17616-17627 - Marco Federici, Ryota Tomioka, Patrick Forré:
An Information-theoretic Approach to Distribution Shifts. 17628-17641 - Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Pan Zhou, Benjamin I. P. Rubinstein, Ce Zhang, Bo Li:
TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness. 17642-17655 - Zhaoqiang Liu, Subhroshekhar Ghosh, Jonathan Scarlett:
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors. 17656-17668 - Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman:
Moser Flow: Divergence-based Generative Modeling on Manifolds. 17669-17680 - Jinyuan Fang, Qiang Zhang, Zaiqiao Meng, Shangsong Liang:
Structure-Aware Random Fourier Kernel for Graphs. 17681-17694 - Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet:
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling. 17695-17709 - Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin:
Improving Transferability of Representations via Augmentation-Aware Self-Supervision. 17710-17722 - Chen Zhu, Wei Ping, Chaowei Xiao, Mohammad Shoeybi, Tom Goldstein, Anima Anandkumar, Bryan Catanzaro:
Long-Short Transformer: Efficient Transformers for Language and Vision. 17723-17736 - Gil Shomron, Freddy Gabbay, Samer Kurzum, Uri C. Weiser:
Post-Training Sparsity-Aware Quantization. 17737-17748 - Rotem Mulayoff, Tomer Michaeli, Daniel Soudry:
The Implicit Bias of Minima Stability: A View from Function Space. 17749-17761 - Gen Li, Laixi Shi, Yuxin Chen, Yuantao Gu, Yuejie Chi:
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning. 17762-17776 - Santiago R. Balseiro, Yuan Deng, Jieming Mao, Vahab S. Mirrokni, Song Zuo:
Robust Auction Design in the Auto-bidding World. 17777-17788 - Toru Hishinuma, Kei Senda:
Weighted model estimation for offline model-based reinforcement learning. 17789-17800 - Julian Katz-Samuels, Blake Mason, Kevin G. Jamieson, Robert Nowak:
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers. 17801-17812 - Siu Lun Chau, Shahine Bouabid, Dino Sejdinovic:
Deconditional Downscaling with Gaussian Processes. 17813-17825 - Ze Wang, Seunghyun Hwang, Zichen Miao, Qiang Qiu:
Image Generation using Continuous Filter Atoms. 17826-17838 - Paul Haider, Benjamin Ellenberger, Laura Kriener, Jakob Jordan, Walter Senn, Mihai A. Petrovici:
Latent Equilibrium: Arbitrarily fast computation with arbitrarily slow neurons. 17839-17851 - Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider
Learning Fast-Inference Bayesian Networks. 17852-17863 - Bowen Cheng, Alexander G. Schwing, Alexander Kirillov:
Per-Pixel Classification is Not All You Need for Semantic Segmentation. 17864-17875 - Amirreza Farnoosh, Sarah Ostadabbas:
Deep Markov Factor Analysis: Towards Concurrent Temporal and Spatial Analysis of fMRI Data. 17876-17888 - Evgenii Egorov, Anna Kuzina, Evgeny Burnaev:
BooVAE: Boosting Approach for Continual Learning of VAE. 17889-17901 - Minjing Dong, Yunhe Wang, Xinghao Chen, Chang Xu:
Handling Long-tailed Feature Distribution in AdderNets. 17902-17912 - Minshuo Chen, Yan Li, Ethan Wang, Zhuoran Yang, Zhaoran Wang, Tuo Zhao:
Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL. 17913-17926 - Gugan Thoppe, Bhumesh Kumar:
A Law of Iterated Logarithm for Multi-Agent Reinforcement Learning. 17927-17938 - Zelun Luo, Wanze Xie, Siddharth Kapoor, Yiyun Liang, Michael Cooper, Juan Carlos Niebles, Ehsan Adeli, Fei-Fei Li:
MOMA: Multi-Object Multi-Actor Activity Parsing. 17939-17955 - Teodor Vanislavov Marinov, Julian Zimmert:
The Pareto Frontier of model selection for general Contextual Bandits. 17956-17967 - Chaoqi Wang, Adish Singla, Yuxin Chen:
Teaching an Active Learner with Contrastive Examples. 17968-17980 - Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg:
Structured Denoising Diffusion Models in Discrete State-Spaces. 17981-17993 - Jesse Mu, Noah D. Goodman:
Emergent Communication of Generalizations. 17994-18007 - Dominic Richards, Sahand Negahban, Patrick Rebeschini:
Distributed Machine Learning with Sparse Heterogeneous Data. 18008-18020 - Ilia Shumailov, Zakhar Shumaylov, Dmitry Kazhdan, Yiren Zhao, Nicolas Papernot, Murat A. Erdogdu, Ross J. Anderson:
Manipulating SGD with Data Ordering Attacks. 18021-18032 - Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann:
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification. 18033-18048 - Zhaozhuo Xu, Beidi Chen, Chaojian Li, Weiyang Liu, Le Song, Yingyan Lin, Anshumali Shrivastava:
Locality Sensitive Teaching. 18049-18062 - Anton Bakhtin, David J. Wu, Adam Lerer, Noam Brown:
No-Press Diplomacy from Scratch. 18063-18074 - Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh:
Remember What You Want to Forget: Algorithms for Machine Unlearning. 18075-18086 - Bohdan Kivva, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam:
Learning latent causal graphs via mixture oracles. 18087-18101 - Hanlin Tang, Yao Li, Ji Liu, Ming Yan:
ErrorCompensatedX: error compensation for variance reduced algorithms. 18102-18113 - Jiahao Li, Bin Li, Yan Lu:
Deep Contextual Video Compression. 18114-18125 - Katja Schwarz, Yiyi Liao, Andreas Geiger:
On the Frequency Bias of Generative Models. 18126-18136 - Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala
Learning curves of generic features maps for realistic datasets with a teacher-student model. 18137-18151 - Regev Cohen, Yochai Blau, Daniel Freedman, Ehud Rivlin:
It Has Potential: Gradient-Driven Denoisers for Convergent Solutions to Inverse Problems. 18152-18164 - Harikrishna Narasimhan, Aditya Krishna Menon:
Training Over-parameterized Models with Non-decomposable Objectives. 18165-18181 - Mateusz Ostaszewski, Lea M. Trenkwalder, Wojciech Masarczyk, Eleanor Scerri, Vedran Dunjko:
Reinforcement learning for optimization of variational quantum circuit architectures. 18182-18194 - Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko:
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices. 18195-18211 - Yana Dranker, He He, Yonatan Belinkov:
IRM - when it works and when it doesn't: A test case of natural language inference. 18212-18224 - Tan Wang, Zhongqi Yue, Jianqiang Huang, Qianru Sun, Hanwang Zhang:
Self-Supervised Learning Disentangled Group Representation as Feature. 18225-18240 - Aaron Chan, Jiashu Xu, Boyuan Long, Soumya Sanyal, Tanishq Gupta, Xiang Ren:
SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoning. 18241-18255 - Corentin Kervadec, Christian Wolf, Grigory Antipov, Moez Baccouche, Madiha Nadri:
Supervising the Transfer of Reasoning Patterns in VQA. 18256-18267 - Edwin Fong, Chris C. Holmes:
Conformal Bayesian Computation. 18268-18279 - Evgenii Chzhen, Christophe Giraud, Gilles Stoltz:
A Unified Approach to Fair Online Learning via Blackwell Approachability. 18280-18292 - Mikkel Abrahamsen, Linda Kleist, Tillmann Miltzow:
Training Neural Networks is ER-complete. 18293-18306 - Yu Bai, Song Mei, Huan Wang, Caiming Xiong:
Understanding the Under-Coverage Bias in Uncertainty Estimation. 18307-18319 - Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar:
Decentralized Q-learning in Zero-sum Markov Games. 18320-18334 - Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh:
Fast Certified Robust Training with Short Warmup. 18335-18349 - Federico López, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard:
Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices. 18350-18366 - Long Zhao, Zizhao Zhang, Ting Chen, Dimitris N. Metaxas, Han Zhang:
Improved Transformer for High-Resolution GANs. 18367-18380 - Xue Yang, Xiaojiang Yang, Jirui Yang, Qi Ming, Wentao Wang, Qi Tian, Junchi Yan:
Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence. 18381-18394 - Sahra Ghalebikesabi, Lucile Ter-Minassian, Karla DiazOrdaz, Chris C. Holmes:
On Locality of Local Explanation Models. 18395-18407 - Bowen Zhang, Yidong Wang, Wenxin Hou, Hao Wu, Jindong Wang, Manabu Okumura, Takahiro Shinozaki:
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling. 18408-18419 - Henning Petzka, Michael Kamp, Linara Adilova, Cristian Sminchisescu, Mario Boley:
Relative Flatness and Generalization. 18420-18432 - Chenjie Cao, Yuxin Hong, Xiang Li, Chengrong Wang, Chengming Xu, Yanwei Fu, Xiangyang Xue:
The Image Local Autoregressive Transformer. 18433-18445 - Xiang Wang, Ying-Xin Wu, An Zhang, Xiangnan He, Tat-Seng Chua:
Towards Multi-Grained Explainability for Graph Neural Networks. 18446-18458 - Hao Liu, Pieter Abbeel:
Behavior From the Void: Unsupervised Active Pre-Training. 18459-18473 - Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn:
Autonomous Reinforcement Learning via Subgoal Curricula. 18474-18486 - Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Statistically and Computationally Efficient Linear Meta-representation Learning. 18487-18500 - Flore Sentenac, Etienne Boursier, Vianney Perchet:
Decentralized Learning in Online Queuing Systems. 18501-18512 - Yizhen Zhang, Minkyu Choi, Kuan Han, Zhongming Liu:
Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning. 18513-18526 - Weizhe Hua, Yichi Zhang, Chuan Guo, Zhiru Zhang, G. Edward Suh:
BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining. 18527-18538 - Gabriele Corso, Zhitao Ying, Michal Pándy, Petar Velickovic, Jure Leskovec, Pietro Liò:
Neural Distance Embeddings for Biological Sequences. 18539-18551 - Guillaume Bellec, Shuqi Wang, Alireza Modirshanechi, Johanni Brea, Wulfram Gerstner:
Fitting summary statistics of neural data with a differentiable spiking network simulator. 18552-18563 - Anish Agarwal, Abdullah Alomar, Varkey Alumootil, Devavrat Shah, Dennis Shen, Zhi Xu, Cindy Yang:
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators. 18564-18576 - Reda Ouhamma, Odalric-Ambrym Maillard, Vianney Perchet:
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits. 18577-18589 - Zihang Jiang, Qibin Hou, Li Yuan, Daquan Zhou, Yujun Shi, Xiaojie Jin, Anran Wang, Jiashi Feng:
All Tokens Matter: Token Labeling for Training Better Vision Transformers. 18590-18602 - Giorgos Bouritsas, Andreas Loukas, Nikolaos Karalias, Michael M. Bronstein:
Partition and Code: learning how to compress graphs. 18603-18619 - Shoulong Zhang
Knowledge-inspired 3D Scene Graph Prediction in Point Cloud. 18620-18632 - Andrew Campbell, Yuyang Shi, Thomas Rainforth, Arnaud Doucet:
Online Variational Filtering and Parameter Learning. 18633-18645 - Hedi Xia, Vai Suliafu, Hangjie Ji, Tan M. Nguyen, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang:
Heavy Ball Neural Ordinary Differential Equations. 18646-18659 - Goutham Rajendran, Bohdan Kivva, Ming Gao, Bryon Aragam:
Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families. 18660-18672 - Alberto Bietti, Luca Venturi, Joan Bruna:
On the Sample Complexity of Learning under Geometric Stability. 18673-18684 - Suraj Kothawade, Nathan Beck, KrishnaTeja Killamsetty, Rishabh K. Iyer:
SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios. 18685-18697 - Samuel Sokota, Caleb Ho, Zaheen Farraz Ahmad, J. Zico Kolter:
Monte Carlo Tree Search With Iteratively Refining State Abstractions. 18698-18709 - Danruo Deng, Guangyong Chen, Jianye Hao, Qiong Wang, Pheng-Ann Heng:
Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning. 18710-18721 - Yaoqing Yang, Liam Hodgkinson, Ryan Theisen, Joe Zou, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney:
Taxonomizing local versus global structure in neural network loss landscapes. 18722-18733 - Alexis Ross, Himabindu Lakkaraju, Osbert Bastani:
Learning Models for Actionable Recourse. 18734-18746 - Patrick Kidger, James Foster, Xuechen Li, Terry J. Lyons:
Efficient and Accurate Gradients for Neural SDEs. 18747-18761 - Juncheng Liu, Kenji Kawaguchi, Bryan Hooi, Yiwei Wang, Xiaokui Xiao:
EIGNN: Efficient Infinite-Depth Graph Neural Networks. 18762-18773 - Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu:
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. 18774-18788 - Agustinus Kristiadi, Matthias Hein, Philipp Hennig:
An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence. 18789-18800 - Tor Lattimore, Botao Hao:
Bandit Phase Retrieval. 18801-18811 - Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions. 18812-18824 - Xin Zhang, Zhuqing Liu, Jia Liu, Zhengyuan Zhu, Songtao Lu:
Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning. 18825-18838 - Han Xie, Jing Ma, Li Xiong, Carl Yang:
Federated Graph Classification over Non-IID Graphs. 18839-18852 - Talip Ucar, Ehsan Hajiramezanali, Lindsay Edwards:
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning. 18853-18865 - Hongjian Wang, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli, Murat A. Erdogdu:
Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance. 18866-18877 - Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, Qiang Liu:
Conflict-Averse Gradient Descent for Multi-task learning. 18878-18890 - Xingyuan Sun, Tianju Xue, Szymon Rusinkiewicz, Ryan P. Adams:
Amortized Synthesis of Constrained Configurations Using a Differentiable Surrogate. 18891-18906 - Dylan J. Foster, Akshay Krishnamurthy:
Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination. 18907-18919 - Jayadev Acharya, Clément L. Canonne, Yuhan Liu
Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition. 18920-18931 - Yury Gorishniy, Ivan Rubachev, Valentin Khrulkov, Artem Babenko:
Revisiting Deep Learning Models for Tabular Data. 18932-18943 - Khoa D. Doan, Yingjie Lao, Ping Li:
Backdoor Attack with Imperceptible Input and Latent Modification. 18944-18957 - Christina J. Yuan, Yash Chandak, Stephen Giguere, Philip S. Thomas, Scott Niekum:
SOPE: Spectrum of Off-Policy Estimators. 18958-18969 - Ganesh Ramachandra Kini, Orestis Paraskevas, Samet Oymak, Christos Thrampoulidis:
Label-Imbalanced and Group-Sensitive Classification under Overparameterization. 18970-18983 - Rohan Mukherjee, Yeming Wen, Dipak Chaudhari, Thomas W. Reps, Swarat Chaudhuri, Christopher M. Jermaine:
Neural Program Generation Modulo Static Analysis. 18984-18996 - Man Zhou, Xueyang Fu, Zeyu Xiao, Gang Yang, Aiping Liu, Zhiwei Xiong:
Unfolding Taylor's Approximations for Image Restoration. 18997-19009 - Hyeon-Jin Park, Seunghun Lee, Sihyeon Kim, Jinyoung Park, Jisu Jeong, Kyung-Min Kim, Jung-Woo Ha, Hyunwoo J. Kim:
Metropolis-Hastings Data Augmentation for Graph Neural Networks. 19010-19020 - Joshua Kavner, Lirong Xia:
Strategic Behavior is Bliss: Iterative Voting Improves Social Welfare. 19021-19032 - Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan:
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations. 19033-19045 - Alexander C. Li, Deepak Pathak:
Functional Regularization for Reinforcement Learning via Learned Fourier Features. 19046-19055 - Kimon Antonakopoulos, Panayotis Mertikopoulos:
Adaptive First-Order Methods Revisited: Convex Minimization without Lipschitz Requirements. 19056-19068 - Hilal Asi, Daniel Levy, John C. Duchi:
Adapting to function difficulty and growth conditions in private optimization. 19069-19081 - Soumyabrata Pal, Arya Mazumdar, Venkata Gandikota:
Support Recovery of Sparse Signals from a Mixture of Linear Measurements. 19082-19094 - Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien:
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity. 19095-19108 - Borja Rodríguez Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund:
Tighter Expected Generalization Error Bounds via Wasserstein Distance. 19109-19121 - Deeksha Adil, Brian Bullins, Sushant Sachdeva:
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization. 19122-19133 - Luca Weihs, Unnat Jain, Iou-Jen Liu, Jordi Salvador, Svetlana Lazebnik, Aniruddha Kembhavi, Alexander G. Schwing:
Bridging the Imitation Gap by Adaptive Insubordination. 19134-19146 - Ecenaz Erdemir, Jeffrey Bickford, Luca Melis, Sergül Aydöre:
Adversarial Robustness with Non-uniform Perturbations. 19147-19159 - Peng Gao, Jiasen Lu, Hongsheng Li, Roozbeh Mottaghi, Aniruddha Kembhavi:
Container: Context Aggregation Networks. 19160-19171 - Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu:
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. 19172-19183 - Mikhail Khodak, Renbo Tu, Tian Li, Liam Li, Maria-Florina Balcan, Virginia Smith, Ameet Talwalkar:
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing. 19184-19197 - Anshul Nasery, Soumyadeep Thakur, Vihari Piratla, Abir De, Sunita Sarawagi:
Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time. 19198-19209 - Georgios Papoudakis, Filippos Christianos, Stefano V. Albrecht:
Agent Modelling under Partial Observability for Deep Reinforcement Learning. 19210-19222 - Weiming Liu, Jiajie Su, Chaochao Chen, Xiaolin Zheng:
Leveraging Distribution Alignment via Stein Path for Cross-Domain Cold-Start Recommendation. 19223-19234 - Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani:
Conservative Offline Distributional Reinforcement Learning. 19235-19247 - Carles Domingo-Enrich, Youssef Mroueh:
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics. 19248-19260 - Aurélien Bibaut, Nathan Kallus, Maria Dimakopoulou, Antoine Chambaz, Mark J. van der Laan:
Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning. 19261-19273 - Wesley J. Maddox, Maximilian Balandat, Andrew Gordon Wilson, Eytan Bakshy:
Bayesian Optimization with High-Dimensional Outputs. 19274-19287 - Chen Ma, Xiangyu Guo, Li Chen, Jun-Hai Yong, Yisen Wang:
Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks. 19288-19300 - Daniel Bolya, Rohit Mittapalli, Judy Hoffman
Scalable Diverse Model Selection for Accessible Transfer Learning. 19301-19312 - Vincent Sitzmann, Semon Rezchikov, Bill Freeman, Josh Tenenbaum, Frédo Durand:
Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering. 19313-19325 - Gengshan Yang, Deqing Sun, Varun Jampani, Daniel Vlasic, Forrester Cole, Ce Liu, Deva Ramanan:
ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction. 19326-19338 - Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans:
Understanding the Effect of Stochasticity in Policy Optimization. 19339-19351 - Sarkhan Badirli, Zeynep Akata, George O. Mohler, Christine Picard, Murat Dundar:
Fine-Grained Zero-Shot Learning with DNA as Side Information. 19352-19362 - Zhengmian Hu, Feihu Huang, Heng Huang:
Optimal Underdamped Langevin MCMC Method. 19363-19374 - Dabeen Lee, Milan Vojnovic:
Scheduling jobs with stochastic holding costs. 19375-19384 - Mihai Fieraru, Mihai Zanfir, Teodor Alexandru Szente, Eduard Gabriel Bazavan, Vlad Olaru, Cristian Sminchisescu:
REMIPS: Physically Consistent 3D Reconstruction of Multiple Interacting People under Weak Supervision. 19385-19397 - Guodong Zhang, Kyle Hsu, Jianing Li, Chelsea Finn, Roger B. Grosse:
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise. 19398-19410 - Alessandro Rudi, Carlo Ciliberto:
PSD Representations for Effective Probability Models. 19411-19422 - Jiaji Huang, Qiang Qiu, Kenneth Church:
Exploiting a Zoo of Checkpoints for Unseen Tasks. 19423-19434 - Qitian Wu, Chenxiao Yang, Junchi Yan:
Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach. 19435-19447 - Fu-En Yang, Yuan-Chia Cheng, Zu-Yun Shiau, Yu-Chiang Frank Wang:
Adversarial Teacher-Student Representation Learning for Domain Generalization. 19448-19460 - Fabien Pesquerel, Hassan Saber, Odalric-Ambrym Maillard:
Stochastic bandits with groups of similar arms. 19461-19472 - Drew Linsley, Girik Malik, Junkyung Kim, Lakshmi Narasimhan Govindarajan, Ennio Mingolla, Thomas Serre:
Tracking Without Re-recognition in Humans and Machines. 19473-19486 - Sameera Ramasinghe, Moshiur R. Farazi, Salman H. Khan, Nick Barnes, Stephen Gould:
Rethinking conditional GAN training: An approach using geometrically structured latent manifolds. 19487-19499 - Louis-Pascal A. C. Xhonneux, Andreea Deac, Petar Velickovic, Jian Tang:
How to transfer algorithmic reasoning knowledge to learn new algorithms? 19500-19512 - Robin Hesse, Simone Schaub-Meyer, Stefan Roth:
Fast Axiomatic Attribution for Neural Networks. 19513-19524 - Chen Zhang, Shifeng Zhang, Fabio Maria Carlucci, Zhenguo Li:
OSOA: One-Shot Online Adaptation of Deep Generative Models for Lossless Compression. 19525-19537 - Kuang-Huei Lee, Anurag Arnab, Sergio Guadarrama, John F. Canny, Ian Fischer:
Compressive Visual Representations. 19538-19552 - Arnab Maiti, Vishakha Patil, Arindam Khan:
Multi-Armed Bandits with Bounded Arm-Memory: Near-Optimal Guarantees for Best-Arm Identification and Regret Minimization. 19553-19565 - Diane Bouchacourt, Mark Ibrahim, Ari S. Morcos:
Grounding inductive biases in natural images: invariance stems from variations in data. 19566-19579 - Zekun Tong, Yuxuan Liang, Henghui Ding
Directed Graph Contrastive Learning. 19580-19593 - Adrian Bulat, Juan-Manuel Pérez-Rúa, Swathikiran Sudhakaran, Brais Martínez, Georgios Tzimiropoulos:
Space-time Mixing Attention for Video Transformer. 19594-19607 - Atsushi Nitanda, Denny Wu, Taiji Suzuki:
Particle Dual Averaging: Optimization of Mean Field Neural Network with Global Convergence Rate Analysis. 19608-19621 - Guiliang Liu, Xiangyu Sun, Oliver Schulte, Pascal Poupart:
Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning. 19622-19636 - Tianyi Chen, Bo Ji, Tianyu Ding, Biyi Fang, Guanyi Wang, Zhihui Zhu, Luming Liang, Yixin Shi, Sheng Yi, Xiao Tu:
Only Train Once: A One-Shot Neural Network Training And Pruning Framework. 19637-19651 - Muchen Li, Leonid Sigal:
Referring Transformer: A One-step Approach to Multi-task Visual Grounding. 19652-19664 - Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen:
Decoupling the Depth and Scope of Graph Neural Networks. 19665-19679 - Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat:
Fast and Memory Efficient Differentially Private-SGD via JL Projections. 19680-19691 - Yu-Lin Tsai, Chia-Yi Hsu, Chia-Mu Yu, Pin-Yu Chen:
Formalizing Generalization and Adversarial Robustness of Neural Networks to Weight Perturbations. 19692-19704 - Guillaume Baudart, Martin Hirzel, Kiran Kate, Parikshit Ram, Avraham Shinnar, Jason Tsay:
Pipeline Combinators for Gradual AutoML. 19705-19718 - Feng Wang, Guoyizhe Wei, Qiao Liu, Jinxiang Ou, Xian Wei, Hairong Lv:
Boost Neural Networks by Checkpoints. 19719-19729 - Ba-Hien Tran, Simone Rossi, Dimitrios Milios, Pietro Michiardi, Edwin V. Bonilla, Maurizio Filippone:
Model Selection for Bayesian Autoencoders. 19730-19742 - Alp Yurtsever, Alex Gu, Suvrit Sra:
Three Operator Splitting with Subgradients, Stochastic Gradients, and Adaptive Learning Rates. 19743-19756 - Mohammad Emtiyaz Khan, Siddharth Swaroop:
Knowledge-Adaptation Priors. 19757-19770 - Chicheng Zhang, Zhi Wang:
Provably efficient multi-task reinforcement learning with model transfer. 19771-19783 - Shitong Luo, Chence Shi, Minkai Xu, Jian Tang:
Predicting Molecular Conformation via Dynamic Graph Score Matching. 19784-19795 - Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. 19796-19807 - Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg:
Bounds all around: training energy-based models with bidirectional bounds. 19808-19821 - Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, Jie Tang:
CogView: Mastering Text-to-Image Generation via Transformers. 19822-19835 - Tyler Farghly, Patrick Rebeschini:
Time-independent Generalization Bounds for SGLD in Non-convex Settings. 19836-19846 - HaiYing Wang, Aonan Zhang, Chong Wang:
Nonuniform Negative Sampling and Log Odds Correction with Rare Events Data. 19847-19859 - Xinxing Wu, Qiang Cheng:
Algorithmic stability and generalization of an unsupervised feature selection algorithm. 19860-19875 - Nikita Polyanskii:
On learning sparse vectors from mixture of responses. 19876-19887 - Ganlin Song, Ruitu Xu, John Lafferty:
Convergence and Alignment of Gradient Descent with Random Backpropagation Weights. 19888-19898 - Han Shu, Jiahao Wang, Hanting Chen, Lin Li, Yujiu Yang
Adder Attention for Vision Transformer. 19899-19909 - Niru Maheswaranathan, David Sussillo, Luke Metz, Ruoxi Sun, Jascha Sohl-Dickstein:
Reverse engineering learned optimizers reveals known and novel mechanisms. 19910-19922 - Jiaqi Zhang, Chandler Squires, Caroline Uhler:
Matching a Desired Causal State via Shift Interventions. 19923-19934 - Hsin-Yi Lin, Huan-Hsin Tseng, Xugang Lu, Yu Tsao:
Unsupervised Noise Adaptive Speech Enhancement by Discriminator-Constrained Optimal Transport. 19935-19946 - Solenne Gaucher, Olga Klopp:
Optimality of variational inference for stochasticblock model with missing links. 19947-19959 - Jingkang Wang, Hongyi Guo, Zhaowei Zhu, Yang Liu:
Policy Learning Using Weak Supervision. 19960-19973 - Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang:
Chasing Sparsity in Vision Transformers: An End-to-End Exploration. 19974-19988 - José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel P. Palomar:
Graphical Models in Heavy-Tailed Markets. 19989-20001 - Xingang Pan, Xudong Xu, Chen Change Loy, Christian Theobalt
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis. 20002-20013 - Alaaeldin Ali, Hugo Touvron, Mathilde Caron, Piotr Bojanowski, Matthijs Douze, Armand Joulin, Ivan Laptev, Natalia Neverova, Gabriel Synnaeve, Jakob Verbeek, Hervé Jégou:
XCiT: Cross-Covariance Image Transformers. 20014-20027 - Lihao Yin, Ganggang Xu, Huiyan Sang, Yongtao Guan:
Row-clustering of a Point Process-valued Matrix. 20028-20039 - Yang Zhang, Ashkan Khakzar, Yawei Li, Azade Farshad, Seong Tae Kim, Nassir Navab:
Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information. 20040-20051 - Maura Pintor, Fabio Roli, Wieland Brendel, Battista Biggio:
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints. 20052-20062 - Rahul Rahaman, Alexandre H. Thiéry:
Uncertainty Quantification and Deep Ensembles. 20063-20075 - Enrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht:
Directed Probabilistic Watershed. 20076-20088 - Erik A. Daxberger, Agustinus Kristiadi, Alexander Immer, Runa Eschenhagen, Matthias Bauer, Philipp Hennig:
Laplace Redux - Effortless Bayesian Deep Learning. 20089-20103 - Zhenyu Liao, Michael W. Mahoney:
Hessian Eigenspectra of More Realistic Nonlinear Models. 20104-20117 - Rati Devidze, Goran Radanovic, Parameswaran Kamalaruban, Adish Singla:
Explicable Reward Design for Reinforcement Learning Agents. 20118-20131 - Scott Fujimoto, Shixiang Shane Gu:
A Minimalist Approach to Offline Reinforcement Learning. 20132-20145 - Rishabh Kabra, Daniel Zoran, Goker Erdogan, Loic Matthey, Antonia Creswell, Matt M. Botvinick, Alexander Lerchner, Christopher P. Burgess:
SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition. 20146-20159 - Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying:
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. 20160-20171 - Badih Ghazi, Ravi Kumar, Pasin Manurangsi:
User-Level Differentially Private Learning via Correlated Sampling. 20172-20184 - Jiyan Jiang, Wenpeng Zhang, Jinjie Gu, Wenwu Zhu:
Asynchronous Decentralized Online Learning. 20185-20196 - Raul Astudillo, Daniel R. Jiang, Maximilian Balandat, Eytan Bakshy, Peter I. Frazier:
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs. 20197-20209 - Alexander Robey, George J. Pappas, Hamed Hassani:
Model-Based Domain Generalization. 20210-20229 - Jiabo He, Sarah M. Erfani, Xingjun Ma, James Bailey, Ying Chi, Xian-Sheng Hua:
$\alpha$-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression. 20230-20242 - David L. Applegate, Mateo Díaz, Oliver Hinder, Haihao Lu, Miles Lubin, Brendan O'Donoghue, Warren Schudy:
Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient. 20243-20257 - Lifu Wang, Bo Shen, Bo Hu, Xing Cao:
On the Provable Generalization of Recurrent Neural Networks. 20258-20269 - Minsu Cho, Aditya Balu, Ameya Joshi, Anjana Deva Prasad, Biswajit Khara, Soumik Sarkar, Baskar Ganapathysubramanian, Adarsh Krishnamurthy
Differentiable Spline Approximations. 20270-20282 - Zhixin Zhou, Fan Zhou, Ping Li, Cun-Hui Zhang:
Rate-Optimal Subspace Estimation on Random Graphs. 20283-20294 - Ari Pakman, Amin Nejatbakhsh, Dar Gilboa, Abdullah Makkeh, Luca Mazzucato, Michael Wibral, Elad Schneidman:
Estimating the Unique Information of Continuous Variables. 20295-20307 - Ignavier Ng, Yujia Zheng, Jiji Zhang, Kun Zhang:
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions. 20308-20320 - Wentao Zhang, Mingyu Yang, Zeang Sheng, Yang Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui:
Node Dependent Local Smoothing for Scalable Graph Learning. 20321-20332 - Vincent Cohen-Addad, Silvio Lattanzi, Ashkan Norouzi-Fard, Christian Sohler
Parallel and Efficient Hierarchical k-Median Clustering. 20333-20345 - Sasha Sheng, Amanpreet Singh, Vedanuj Goswami, Jose Alberto Lopez Magana, Tristan Thrush, Wojciech Galuba, Devi Parikh, Douwe Kiela:
Human-Adversarial Visual Question Answering. 20346-20359 - Pedro Herrero-Vidal, Dmitry Rinberg, Cristina Savin:
Across-animal odor decoding by probabilistic manifold alignment. 20360-20372 - Naren Manoj, Avrim Blum:
Excess Capacity and Backdoor Poisoning. 20373-20384 - Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi:
A Convergence Analysis of Gradient Descent on Graph Neural Networks. 20385-20397 - Quentin Le Lidec, Ivan Laptev, Cordelia Schmid, Justin Carpentier:
Differentiable rendering with perturbed optimizers. 20398-20409 - Yang Zhang, Bo Tang, Qingyu Yang, Dou An, Hongyin Tang, Chenyang Xi, Xueying Li, Feiyu Xiong:
BCORLE(λ): An Offline Reinforcement Learning and Evaluation Framework for Coupons Allocation in E-commerce Market. 20410-20422 - Heiko Zimmermann, Hao Wu, Babak Esmaeili, Jan-Willem van de Meent:
Nested Variational Inference. 20423-20435 - Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang:
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning. 20436-20446 - Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun:
On sensitivity of meta-learning to support data. 20447-20460 - Zachary Charles, Zachary Garrett, Zhouyuan Huo, Sergei Shmulyian, Virginia Smith:
On Large-Cohort Training for Federated Learning. 20461-20475 - Yuhong Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen:
Generic Neural Architecture Search via Regression. 20476-20490 - Tiancheng Jin, Longbo Huang, Haipeng Luo:
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition. 20491-20502 - Yihui Quek, Srinivasan Arunachalam, John A. Smolin:
Private learning implies quantum stability. 20503-20515 - Simone Parisi, Victoria Dean, Deepak Pathak, Abhinav Gupta:
Interesting Object, Curious Agent: Learning Task-Agnostic Exploration. 20516-20530 - Heyang Qin, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He:
SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement. 20531-20544 - Lukas Köhs, Bastian Alt
Variational Inference for Continuous-Time Switching Dynamical Systems. 20545-20557 - Fan Wu, Patrick Rebeschini:
Implicit Regularization in Matrix Sensing via Mirror Descent. 20558-20570 - Kfir Y. Levy, Ali Kavis, Volkan Cevher
STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization. 20571-20582 - Yujia Yan, Frank Cwitkowitz, Zhiyao Duan:
Skipping the Frame-Level: Event-Based Piano Transcription With Neural Semi-CRFs. 20583-20595 - Mansheej Paul, Surya Ganguli, Gintare Karolina Dziugaite:
Deep Learning on a Data Diet: Finding Important Examples Early in Training. 20596-20607 - Qi Qin, Wenpeng Hu, Han Peng, Dongyan Zhao, Bing Liu:
BNS: Building Network Structures Dynamically for Continual Learning. 20608-20620 - Bashir Rastegarpanah, Krishna P. Gummadi
Auditing Black-Box Prediction Models for Data Minimization Compliance. 20621-20632 - Lee Cohen, Ulrike Schmidt-Kraepelin, Yishay Mansour:
Dueling Bandits with Team Comparisons. 20633-20644 - Raphael Bensadoun, Shir Gur, Tomer Galanti, Lior Wolf:
Meta Internal Learning. 20645-20656 - Frederic Koehler, Lijia Zhou, Danica J. Sutherland, Nathan Srebro:
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds and Benign Overfitting. 20657-20668 - Wooseok Ha, Chandan Singh, François Lanusse, Srigokul Upadhyayula, Bin Yu:
Adaptive wavelet distillation from neural networks through interpretations. 20669-20682 - Xudong Xu, Xingang Pan, Dahua Lin, Bo Dai:
Generative Occupancy Fields for 3D Surface-Aware Image Synthesis. 20683-20695 - Ryan McKenna, Siddhant Pradhan, Daniel Sheldon, Gerome Miklau:
Relaxed Marginal Consistency for Differentially Private Query Answering. 20696-20707 - Sarah Müller, Alexander von Rohr
Local policy search with Bayesian optimization. 20708-20720 - Wei Sun, Aojun Zhou, Sander Stuijk, Rob G. J. Wijnhoven, Andrew Nelson, Hongsheng Li, Henk Corporaal:
DominoSearch: Find layer-wise fine-grained N: M sparse schemes from dense neural networks. 20721-20732 - Sever Topan, David Rolnick, Xujie Si:
Techniques for Symbol Grounding with SATNet. 20733-20744 - Yue Wang, Justin M. Solomon:
Object DGCNN: 3D Object Detection using Dynamic Graphs. 20745-20758 - Akifumi Wachi, Yunyue Wei, Yanan Sui:
Safe Policy Optimization with Local Generalized Linear Function Approximations. 20759-20771 - Takashi Matsubara, Yuto Miyatake, Takaharu Yaguchi:
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory. 20772-20784 - Grzegorz Gluch, Rüdiger L. Urbanke:
Exponential Separation between Two Learning Models and Adversarial Robustness. 20785-20797 - Werner Zellinger, Natalia Shepeleva, Marius-Constantin Dinu, Hamid Eghbal-zadeh, Hoan Duc Nguyen, Bernhard Nessler, Sergei V. Pereverzyev, Bernhard Alois Moser:
The balancing principle for parameter choice in distance-regularized domain adaptation. 20798-20811 - Yuhui Quan, Zicong Wu, Hui Ji:
Gaussian Kernel Mixture Network for Single Image Defocus Deblurring. 20812-20824 - Frank Schneider, Felix Dangel, Philipp Hennig:
Cockpit: A Practical Debugging Tool for the Training of Deep Neural Networks. 20825-20837 - Geng Yuan, Xiaolong Ma, Wei Niu, Zhengang Li, Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, Siyue Wang, Minghai Qin, Bin Ren, Yanzhi Wang, Sijia Liu, Xue Lin:
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge. 20838-20850 - Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann:
Precise characterization of the prior predictive distribution of deep ReLU networks. 20851-20862 - Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
RED : Looking for Redundancies for Data-FreeStructured Compression of Deep Neural Networks. 20863-20873 - Yu Li, Min Li, Qiuxia Lai, Yannan Liu, Qiang Xu:
TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks. 20874-20886 - Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim:
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods. 20887-20902 - Krishnakant V. Saboo, Anirudh Choudhary, Yurui Cao, Gregory A. Worrell, David T. Jones, Ravishankar K. Iyer:
Reinforcement Learning based Disease Progression Model for Alzheimer's Disease. 20903-20915 - Gal Greshler, Tamar Rott Shaham, Tomer Michaeli:
Catch-A-Waveform: Learning to Generate Audio from a Single Short Example. 20916-20928 - Sandareka Wickramanayake, Wynne Hsu, Mong-Li Lee:
Explanation-based Data Augmentation for Image Classification. 20929-20940 - Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, Zhangyang Wang:
Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspective. 20941-20955 - Quynh Nguyen, Pierre Bréchet, Marco Mondelli:
When Are Solutions Connected in Deep Networks? 20956-20969 - Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, William K. Cheung, James T. Kwok:
TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation. 20970-20982 - Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Learning Graph Cellular Automata. 20983-20994 - Shantanu Gupta, Zachary C. Lipton, David Childers:
Efficient Online Estimation of Causal Effects by Deciding What to Observe. 20995-21007 - Vudtiwat Ngampruetikorn, David J. Schwab:
Perturbation Theory for the Information Bottleneck. 21008-21018 - Jia Li, Jiajin Li, Yang Liu, Jianwei Yu, Yueting Li, Hong Cheng:
Deconvolutional Networks on Graph Data. 21019-21030 - Jiayi Shen, Xiantong Zhen, Marcel Worring, Ling Shao:
Variational Multi-Task Learning with Gumbel-Softmax Priors. 21031-21042 - Jeffrey Ichnowski, Paras Jain, Bartolomeo Stellato, Goran Banjac, Michael Luo, Francesco Borrelli, Joseph E. Gonzalez, Ion Stoica, Ken Goldberg:
Accelerating Quadratic Optimization with Reinforcement Learning. 21043-21055 - Wei Fang, Zhaofei Yu, Yanqi Chen, Tiejun Huang, Timothée Masquelier, Yonghong Tian:
Deep Residual Learning in Spiking Neural Networks. 21056-21069 - Zaixiang Zheng, Hao Zhou, Shujian Huang, Jiajun Chen, Jingjing Xu, Lei Li:
Duplex Sequence-to-Sequence Learning for Reversible Machine Translation. 21070-21084 - Vincent Cohen-Addad, David Saulpic, Chris Schwiegelshohn:
Improved Coresets and Sublinear Algorithms for Power Means in Euclidean Spaces. 21085-21098 - Itay Hubara, Brian Chmiel, Moshe Island, Ron Banner, Joseph Naor, Daniel Soudry:
Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N: M Transposable Masks. 21099-21111 - Abhishek Panigrahi, Navin Goyal:
Learning and Generalization in RNNs. 21112-21124 - Yanhong Zeng, Huan Yang, Hongyang Chao, Jianbo Wang, Jianlong Fu:
Improving Visual Quality of Image Synthesis by A Token-based Generator with Transformers. 21125-21137 - Fabian Latorre, Leello Tadesse Dadi, Paul Rolland, Volkan Cevher
The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers. 21138-21149 - Hang Xu, Kelly Kostopoulou, Aritra Dutta, Xin Li, Alexandros Ntoulas, Panos Kalnis:
DeepReduce: A Sparse-tensor Communication Framework for Federated Deep Learning. 21150-21163 - Lingxiao Wang, Zhuoran Yang, Zhaoran Wang:
Provably Efficient Causal Reinforcement Learning with Confounded Observational Data. 21164-21175 - Yair Schiff, Brian Quanz, Payel Das, Pin-Yu Chen:
Predicting Deep Neural Network Generalization with Perturbation Response Curves. 21176-21188 - Manh-Ha Bui, Toan Tran, Anh Tran, Dinh Q. Phung:
Exploiting Domain-Specific Features to Enhance Domain Generalization. 21189-21201 - Sattar Vakili, Nacime Bouziani, Sepehr Jalali, Alberto Bernacchia, Da-Shan Shiu:
Optimal Order Simple Regret for Gaussian Process Bandits. 21202-21215 - Yunwen Lei, Mingrui Liu, Yiming Ying:
Generalization Guarantee of SGD for Pairwise Learning. 21216-21228 - Junya Chen, Zidi Xiu, Benjamin Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao:
Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer. 21229-21243 - Bingcong Li, Alireza Sadeghi, Georgios B. Giannakis:
Heavy Ball Momentum for Conditional Gradient. 21244-21255 - Cheng-I Jeff Lai, Yang Zhang, Alexander H. Liu, Shiyu Chang, Yi-Lun Liao, Yung-Sung Chuang, Kaizhi Qian, Sameer Khurana, David D. Cox, James R. Glass:
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition. 21256-21272 - Wenshuo Guo, Michael I. Jordan, Emmanouil Zampetakis
Robust Learning of Optimal Auctions. 21273-21284 - Ido Galil, Ran El-Yaniv:
Disrupting Deep Uncertainty Estimation Without Harming Accuracy. 21285-21296 - Jiachen Lu, Jinghan Yao, Junge Zhang, Xiatian Zhu, Hang Xu, Weiguo Gao, Chunjing Xu, Tao Xiang, Li Zhang:
SOFT: Softmax-free Transformer with Linear Complexity. 21297-21309 - Wonyong Jeong, Hayeon Lee, Geon Park, Eunyoung Hyung, Jinheon Baek, Sung Ju Hwang:
Task-Adaptive Neural Network Search with Meta-Contrastive Learning. 21310-21324 - Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann:
Neural Flows: Efficient Alternative to Neural ODEs. 21325-21337 - Feiyang Ye, Baijiong Lin, Zhixiong Yue, Pengxin Guo, Qiao Xiao, Yu Zhang:
Multi-Objective Meta Learning. 21338-21351 - Gadi Naveh, Zohar Ringel:
A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs. 21352-21364 - Andreis Bruno, Jeffrey Willette, Juho Lee, Sung Ju Hwang:
Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding. 21365-21374 - Michael Kapralov
Efficient and Local Parallel Random Walks. 21375-21387 - Abhinav Agrawal, Justin Domke:
Amortized Variational Inference for Simple Hierarchical Models. 21388-21399 - Nathan Noiry, Vianney Perchet, Flore Sentenac:
Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm. 21400-21412 - Subhadip Mukherjee, Marcello Carioni, Ozan Öktem, Carola-Bibiane Schönlieb:
End-to-end reconstruction meets data-driven regularization for inverse problems. 21413-21425 - Lawrence K. Saul:
An online passive-aggressive algorithm for difference-of-squares classification. 21426-21439 - Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators. 21440-21452 - Runzhong Wang, Zhigang Hua, Gan Liu, Jiayi Zhang, Junchi Yan, Feng Qi, Shuang Yang, Jun Zhou, Xiaokang Yang:
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs. 21453-21466 - Shaogao Lv, Junhui Wang, Jiankun Liu, Yong Liu:
Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation. 21467-21479 - Lijie Fan, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Chuang Gan:
When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning? 21480-21492 - Yihan Zeng, Chunwei Wang, Yunbo Wang, Hang Xu, Chaoqiang Ye, Zhen Yang, Chao Ma:
Learning Transferable Features for Point Cloud Detection via 3D Contrastive Co-training. 21493-21504 - Victor Zhong, Austin W. Hanjie, Sida I. Wang, Karthik Narasimhan, Luke Zettlemoyer:
SILG: The Multi-domain Symbolic Interactive Language Grounding Benchmark. 21505-21519 - Kai Yan, Jie Yan, Chuan Luo, Liting Chen, Qingwei Lin, Dongmei Zhang:
A Surrogate Objective Framework for Prediction+Programming with Soft Constraints. 21520-21532 - Yan Luo, Yongkang Wong, Mohan S. Kankanhalli, Qi Zhao:
Learning to Predict Trustworthiness with Steep Slope Loss. 21533-21544 - Ekaterina Lobacheva, Maxim Kodryan, Nadezhda Chirkova, Andrey Malinin, Dmitry P. Vetrov:
On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay. 21545-21556 - Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava:
NeRV: Neural Representations for Videos. 21557-21568 - Rafael M. Frongillo, Bo Waggoner:
Surrogate Regret Bounds for Polyhedral Losses. 21569-21580 - Aditya Vardhan Varre, Loucas Pillaud-Vivien, Nicolas Flammarion:
Last iterate convergence of SGD for Least-Squares in the Interpolation regime. 21581-21591 - Mohammadamin Banayeeanzade, Rasoul Mirzaiezadeh, Hosein Hasani, Mahdieh Soleymani:
Generative vs. Discriminative: Rethinking The Meta-Continual Learning. 21592-21604 - Antoine Bodin, Nicolas Macris:
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model. 21605-21617 - Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou:
Rethinking Graph Transformers with Spectral Attention. 21618-21629 - Itai Gat, Idan Schwartz, Alexander G. Schwing:
Perceptual Score: What Data Modalities Does Your Model Perceive? 21630-21643 - Robin M. E. Swezey, Aditya Grover, Bruno Charron, Stefano Ermon:
PiRank: Scalable Learning To Rank via Differentiable Sorting. 21644-21654 - Liming Jiang, Bo Dai, Wayne Wu, Chen Change Loy:
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data. 21655-21667 - Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Karthikeyan Shanmugam
CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions. 21668-21680 - Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller:
Iterative Teaching by Label Synthesis. 21681-21695 - Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho:
On Density Estimation with Diffusion Models. 21696-21707 - Yichong Leng, Xu Tan, Linchen Zhu, Jin Xu, Renqian Luo, Linquan Liu, Tao Qin, Xiangyang Li, Edward Lin, Tie-Yan Liu:
FastCorrect: Fast Error Correction with Edit Alignment for Automatic Speech Recognition. 21708-21719 - Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Kernelized Heterogeneous Risk Minimization. 21720-21731 - Nico Gürtler, Dieter Büchler, Georg Martius:
Hierarchical Reinforcement Learning with Timed Subgoals. 21732-21743 - Bo Li, Minming Li, Ruilong Zhang:
Fair Scheduling for Time-dependent Resources. 21744-21756 - Bahjat Kawar, Gregory Vaksman, Michael Elad:
SNIPS: Solving Noisy Inverse Problems Stochastically. 21757-21769 - Alejandro F. Queiruga, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney:
Stateful ODE-Nets using Basis Function Expansions. 21770-21781 - Chanwoo Lee, Miaoyan Wang:
Beyond the Signs: Nonparametric Tensor Completion via Sign Series. 21782-21794 - Chao Ma, José Miguel Hernández-Lobato:
Functional Variational Inference based on Stochastic Process Generators. 21795-21807 - Yuejiang Liu, Parth Kothari, Bastien van Delft, Baptiste Bellot-Gurlet, Taylor Mordan, Alexandre Alahi:
TTT++: When Does Self-Supervised Test-Time Training Fail or Thrive? 21808-21820 - Yonghan Jung, Jin Tian, Elias Bareinboim:
Double Machine Learning Density Estimation for Local Treatment Effects with Instruments. 21821-21833 - Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu:
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks. 21834-21846 - Murtaza Dalal, Deepak Pathak, Ruslan Salakhutdinov:
Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives. 21847-21859 - Runtian Zhai, Chen Dan, Arun Sai Suggala, J. Zico Kolter, Pradeep Ravikumar:
Boosted CVaR Classification. 21860-21871 - Haoyang Li, Xin Wang, Ziwei Zhang, Zehuan Yuan, Hang Li, Wenwu Zhu:
Disentangled Contrastive Learning on Graphs. 21872-21884 - Lin Guan, Mudit Verma, Sihang Guo, Ruohan Zhang, Subbarao Kambhampati:
Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation. 21885-21897 - Bin Dong, Fangao Zeng, Tiancai Wang, Xiangyu Zhang, Yichen Wei:
SOLQ: Segmenting Objects by Learning Queries. 21898-21909 - Yaofeng Desmond Zhong, Biswadip Dey, Amit Chakraborty:
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models. 21910-21922 - Cristóbal Guzmán, Nishant A. Mehta, Ali Mortazavi:
Best-case lower bounds in online learning. 21923-21934 - Zhiqiang Xu, Ping Li:
A Comprehensively Tight Analysis of Gradient Descent for PCA. 21935-21946 - Khang Le, Huy Nguyen, Quang Minh Nguyen, Tung Pham, Hung Bui, Nhat Ho:
On Robust Optimal Transport: Computational Complexity and Barycenter Computation. 21947-21959 - Alan Malek, Silvia Chiappa:
Asymptotically Best Causal Effect Identification with Multi-Armed Bandits. 21960-21971 - Brandon McMahan, Michael Kleinman, Jonathan C. Kao:
Learning rule influences recurrent network representations but not attractor structure in decision-making tasks. 21972-21983 - Gengwei Zhang, Guoliang Kang, Yi Yang, Yunchao Wei:
Few-Shot Segmentation via Cycle-Consistent Transformer. 21984-21996 - Pál András Papp, Karolis Martinkus, Lukas Faber, Roger Wattenhofer:
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks. 21997-22009 - Ruben Ohana, Hamlet Jesse Medina Ruiz, Julien Launay, Alessandro Cappelli, Iacopo Poli, Liva Ralaivola, Alain Rakotomamonjy:
Photonic Differential Privacy with Direct Feedback Alignment. 22010-22020 - Chenxin Tao, Zizhang Li, Xizhou Zhu, Gao Huang, Yong Liu, Jifeng Dai:
Searching Parameterized AP Loss for Object Detection. 22021-22033 - Jackie Baek, Vivek F. Farias:
Fair Exploration via Axiomatic Bargaining. 22034-22045 - Jessica Finocchiaro, Rafael M. Frongillo, Bo Waggoner:
Unifying lower bounds on prediction dimension of convex surrogates. 22046-22057 - Marc T. Law:
Ultrahyperbolic Neural Networks. 22058-22069 - Jayant Jain, Vrittika Bagadia, Sahil Manchanda, Sayan Ranu:
NeuroMLR: Robust & Reliable Route Recommendation on Road Networks. 22070-22082 - Heyuan Liu, Paul Grigas:
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method. 22083-22094 - Julien Boussard, Erdem Varol, Hyun Dong Lee, Nishchal Dethe, Liam Paninski:
Three-dimensional spike localization and improved motion correction for Neuropixels recordings. 22095-22105 - Hanzhe Hu, Fangyun Wei, Han Hu, Qiwei Ye, Jinshi Cui, Liwei Wang:
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning. 22106-22118 - Yifan Hu, Xin Chen, Niao He:
On the Bias-Variance-Cost Tradeoff of Stochastic Optimization. 22119-22131 - Jason M. Altschuler, Sinho Chewi, Patrik Gerber, Austin J. Stromme:
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent. 22132-22145 - James Bell, Linda Linsefors, Caspar Oesterheld, Joar Skalse:
Reinforcement Learning in Newcomblike Environments. 22146-22157 - Xiang Deng, Zhongfei Zhang:
Comprehensive Knowledge Distillation with Causal Intervention. 22158-22170 - Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin:
Reinforcement Learning with Latent Flow. 22171-22183 - Kyle Aitken, Vinay V. Ramasesh, Yuan Cao, Niru Maheswaranathan:
Understanding How Encoder-Decoder Architectures Attend. 22184-22195 - Xinyun Chen, Dawn Song, Yuandong Tian:
Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages. 22196-22208 - Chris Gagne, Peter Dayan:
Two steps to risk sensitivity. 22209-22220 - Boris van Breugel, Trent Kyono, Jeroen Berrevoets, Mihaela van der Schaar:
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks. 22221-22233 - Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization. 22234-22246 - Danil Tyulmankov, Ching Fang, Annapurna Vadaparty, Guangyu Robert Yang:
Biological key-value memory networks. 22247-22258 - Miklós Z. Rácz, Anirudh Sridhar:
Correlated Stochastic Block Models: Exact Graph Matching with Applications to Recovering Communities. 22259-22273 - Esther Derman, Matthieu Geist, Shie Mannor:
Twice regularized MDPs and the equivalence between robustness and regularization. 22274-22287 - Jiafan He, Dongruo Zhou, Quanquan Gu:
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs. 22288-22300 - Yan Sun, Wenjun Xiong, Faming Liang:
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration. 22301-22312 - Shengjia Zhao, Michael P. Kim, Roshni Sahoo, Tengyu Ma, Stefano Ermon:
Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration. 22313-22324 - Dmitry Kovalev, Elnur Gasanov, Alexander V. Gasnikov, Peter Richtárik:
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks. 22325-22335 - Yash Pote, Kuldeep S. Meel:
Testing Probabilistic Circuits. 22336-22347 - Lantao Yu, Jiaming Song, Yang Song, Stefano Ermon:
Pseudo-Spherical Contrastive Divergence. 22348-22362 - Pranay Manocha, Buye Xu, Anurag Kumar:
NORESQA: A Framework for Speech Quality Assessment using Non-Matching References. 22363-22378 - Liyuan Wang, Mingtian Zhang, Zhongfan Jia, Qian Li, Chenglong Bao, Kaisheng Ma, Jun Zhu, Yi Zhong:
AFEC: Active Forgetting of Negative Transfer in Continual Learning. 22379-22391 - Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang:
Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization. 22392-22404 - Junbum Cha, Sanghyuk Chun, Kyungjae Lee, Han-Cheol Cho, Seunghyun Park, Yunsung Lee, Sungrae Park:
SWAD: Domain Generalization by Seeking Flat Minima. 22405-22418 - Haixu Wu, Jiehui Xu, Jianmin Wang
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting. 22419-22430 - Qianli Xu, Fen Fang, Ana Garcia del Molino, Vigneshwaran Subbaraju, Joo-Hwee Lim:
Predicting Event Memorability from Contextual Visual Semantics. 22431-22442 - Zixuan Ke, Bing Liu, Nianzu Ma, Hu Xu, Lei Shu:
Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning. 22443-22456 - Rianne de Heide, James Cheshire, Pierre Ménard, Alexandra Carpentier:
Bandits with many optimal arms. 22457-22469 - Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai:
Combiner: Full Attention Transformer with Sparse Computation Cost. 22470-22482 - Guandao Yang, Serge J. Belongie, Bharath Hariharan, Vladlen Koltun:
Geometry Processing with Neural Fields. 22483-22497 - Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasin Manurangsi, Renato Paes Leme, Jon Schneider:
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms. 22498-22508 - Xiaolin Hu, Kai Li, Weiyi Zhang, Yi Luo, Jean-Marie Lemercier, Timo Gerkmann:
Speech Separation Using an Asynchronous Fully Recurrent Convolutional Neural Network. 22509-22522 - Caihua Shan, Yifei Shen, Yao Zhang, Xiang Li, Dongsheng Li:
Reinforcement Learning Enhanced Explainer for Graph Neural Networks. 22523-22533 - Shen Yan, Colin White, Yash Savani, Frank Hutter:
NAS-Bench-x11 and the Power of Learning Curves. 22534-22549 - Yinglun Xu, Bhuvesh Kumar, Jacob D. Abernethy:
Observation-Free Attacks on Stochastic Bandits. 22550-22561 - Changhao Shi, Sivan Schwartz, Shahar Levy, Shay Achvat, Maisan Abboud, Amir Ghanayim, Jackie Schiller, Gal Mishne:
Learning Disentangled Behavior Embeddings. 22562-22573 - Yujin Tang, David Ha:
The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning. 22574-22587 - Sucheol Lee, Donghwan Kim:
Fast Extra Gradient Methods for Smooth Structured Nonconvex-Nonconcave Minimax Problems. 22588-22600 - Junjie Ma, Ji Xu, Arian Maleki:
Analysis of Sensing Spectral for Signal Recovery under a Generalized Linear Model. 22601-22613 - Irwan Bello, William Fedus, Xianzhi Du, Ekin Dogus Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph:
Revisiting ResNets: Improved Training and Scaling Strategies. 22614-22627 - Lucas Liebenwein, Ramin M. Hasani, Alexander Amini, Daniela Rus:
Sparse Flows: Pruning Continuous-depth Models. 22628-22642 - Guangpin Tao, Xiaozhong Ji, Wenzhuo Wang, Shuo Chen, Chuming Lin, Yun Cao, Tong Lu, Donghao Luo, Ying Tai:
Spectrum-to-Kernel Translation for Accurate Blind Image Super-Resolution. 22643-22654 - Angeliki Giannou, Emmanouil V. Vlatakis-Gkaragkounis
The convergence rate of regularized learning in games: From bandits and uncertainty to optimism and beyond. 22655-22666 - Bahare Fatemi, Layla El Asri, Seyed Mehran Kazemi:
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks. 22667-22681 - Fangyun Wei, Yue Gao, Zhirong Wu, Han Hu, Stephen Lin:
Aligning Pretraining for Detection via Object-Level Contrastive Learning. 22682-22694 - Greg Lewis, Vasilis Syrgkanis:
Double/Debiased Machine Learning for Dynamic Treatment Effects. 22695-22707 - Travers Rhodes, Daniel D. Lee:
Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization. 22708-22719 - Andrea Zanette, Kefan Dong, Jonathan N. Lee, Emma Brunskill:
Design of Experiments for Stochastic Contextual Linear Bandits. 22720-22731 - Yong Xu, Feng Li, Zhile Chen, Jinxiu Liang, Yuhui Quan:
Encoding Spatial Distribution of Convolutional Features for Texture Representation. 22732-22744 - Yujia Huang, Huan Zhang, Yuanyuan Shi, J. Zico Kolter, Anima Anandkumar:
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds. 22745-22757 - Yi Wan, Abhishek Naik, Richard S. Sutton:
Average-Reward Learning and Planning with Options. 22758-22769 - Muhammad Akhtar Munir, Muhammad Haris Khan, M. Saquib Sarfraz, Mohsen Ali:
SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection. 22770-22782 - Briti Gangopadhyay, Pallab Dasgupta:
Counterexample Guided RL Policy Refinement Using Bayesian Optimization. 22783-22794 - Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu:
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. 22795-22807 - Giorgia Ramponi, Alberto Maria Metelli, Alessandro Concetti, Marcello Restelli:
Learning in Non-Cooperative Configurable Markov Decision Processes. 22808-22821 - Jeffrey Adams, Niels Hansen, Kun Zhang:
Identification of Partially Observed Linear Causal Models: Graphical Conditions for the Non-Gaussian and Heterogeneous Cases. 22822-22833 - Wenzheng Chen, Joey Litalien, Jun Gao, Zian Wang, Clement Fuji Tsang, Sameh Khamis, Or Litany, Sanja Fidler:
DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer. 22834-22848 - Lingxiao Huang, K. Sudhir, Nisheeth K. Vishnoi:
Coresets for Time Series Clustering. 22849-22862 - Chin-Wei Huang, Jae Hyun Lim, Aaron C. Courville:
A Variational Perspective on Diffusion-Based Generative Models and Score Matching. 22863-22876 - Giulia DeSalvo, Claudio Gentile, Tobias Sommer Thune:
Online Active Learning with Surrogate Loss Functions. 22877-22889 - Zhao Song, Shuo Yang, Ruizhe Zhang:
Does Preprocessing Help Training Over-parameterized Neural Networks? 22890-22904 - Maximilian Seitzer, Bernhard Schölkopf, Georg Martius:
Causal Influence Detection for Improving Efficiency in Reinforcement Learning. 22905-22918 - Yoon-Yeong Kim, Kyungwoo Song, JoonHo Jang, Il-Chul Moon:
LADA: Look-Ahead Data Acquisition via Augmentation for Deep Active Learning. 22919-22930 - Haipeng Luo, Chen-Yu Wei, Chung-Wei Lee:
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses. 22931-22942 - Satchit Sivakumar, Mark Bun, Marco Gaboardi
Multiclass versus Binary Differentially Private PAC Learning. 22943-22954 - Mengchu Li, Yi Yu:
Adversarially Robust Change Point Detection. 22955-22967 - Hong Liu, Jianmin Wang
Cycle Self-Training for Domain Adaptation. 22968-22981 - Bingchen Zhao, Kai Han:
Novel Visual Category Discovery with Dual Ranking Statistics and Mutual Knowledge Distillation. 22982-22994 - Fuchao Wei, Chenglong Bao, Yang Liu:
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization. 22995-23008 - Bingyan Wang, Yuling Yan, Jianqing Fan:
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model. 23009-23022 - Evan McCarty, Qi Zhao, Anastasios Sidiropoulos, Yusu Wang:
NN-Baker: A Neural-network Infused Algorithmic Framework for Optimization Problems on Geometric Intersection Graphs. 23023-23035 - Yunfeng Cai, Guanhua Fang, Ping Li:
A Note on Sparse Generalized Eigenvalue Problem. 23036-23048 - Wei Qiu, Xinrun Wang, Runsheng Yu, Rundong Wang, Xu He, Bo An, Svetlana Obraztsova, Zinovi Rabinovich:
RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents. 23049-23062 - Alexander Matt Turner, Logan Smith, Rohin Shah, Andrew Critch, Prasad Tadepalli:
Optimal Policies Tend To Seek Power. 23063-23074 - Lukasz Kucinski, Tomasz Korbak, Pawel Kolodziej, Piotr Milos:
Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication. 23075-23088 - Zimin Chen, Vincent J. Hellendoorn, Pascal Lamblin, Petros Maniatis, Pierre-Antoine Manzagol, Daniel Tarlow, Subhodeep Moitra:
PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair. 23089-23101 - Yu Meng, Chenyan Xiong, Payal Bajaj, Saurabh Tiwary, Paul Bennett, Jiawei Han, Xia Song:
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining. 23102-23114 - Qi Deng, Wenzhi Gao:
Minibatch and Momentum Model-based Methods for Stochastic Weakly Convex Optimization. 23115-23127 - Stephen McAleer, John B. Lanier, Kevin A. Wang, Pierre Baldi, Roy Fox:
XDO: A Double Oracle Algorithm for Extensive-Form Games. 23128-23139 - Vihari Piratla, Soumen Chakrabarti, Sunita Sarawagi:
Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations. 23140-23151 - Michael Kleinman, Chandramouli Chandrasekaran, Jonathan C. Kao:
A mechanistic multi-area recurrent network model of decision-making. 23152-23165 - Nan Liu, Shuang Li, Yilun Du, Josh Tenenbaum, Antonio Torralba:
Learning to Compose Visual Relations. 23166-23178 - Róbert Busa-Fekete, Dimitris Fotakis, Balázs Szörényi, Emmanouil Zampetakis
Identity testing for Mallows model. 23179-23190 - Karthik Abinav Sankararaman, Aleksandrs Slivkins:
Bandits with Knapsacks beyond the Worst Case. 23191-23204 - Yuchao Qin, Fergus Imrie, Alihan Hüyük, Daniel Jarrett, Alexander Gimson, Mihaela van der Schaar:
Closing the loop in medical decision support by understanding clinical decision-making: A case study on organ transplantation. 23205-23217 - Arwa Alanqary, Abdullah Alomar, Devavrat Shah:
Change Point Detection via Multivariate Singular Spectrum Analysis. 23218-23230 - Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David Duvenaud:
Meta-learning to Improve Pre-training. 23231-23244 - Adarsh Barik, Jean Honorio
Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem. 23245-23257 - Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama:
Probabilistic Margins for Instance Reweighting in Adversarial Training. 23258-23269 - Laetitia Chapel, Rémi Flamary, Haoran Wu, Cédric Févotte, Gilles Gasso:
Unbalanced Optimal Transport through Non-negative Penalized Linear Regression. 23270-23282 - Georg Ostrovski, Pablo Samuel Castro, Will Dabney:
The Difficulty of Passive Learning in Deep Reinforcement Learning. 23283-23295 - Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang:
Intriguing Properties of Vision Transformers. 23296-23308 - Benyuan Sun, Hongxing Huo, Yi Yang, Bo Bai:
PartialFed: Cross-Domain Personalized Federated Learning via Partial Initialization. 23309-23320 - Jialin Zhao, Yuxiao Dong, Ming Ding, Evgeny Kharlamov, Jie Tang:
Adaptive Diffusion in Graph Neural Networks. 23321-23333 - Orestis Papadigenopoulos, Constantine Caramanis:
Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits. 23334-23346 - Yi Sui, Ga Wu, Scott Sanner:
Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models. 23347-23358 - Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry:
Editing a classifier by rewriting its prediction rules. 23359-23373 - Vanessa D'Amario, Tomotake Sasaki, Xavier Boix:
How Modular should Neural Module Networks Be for Systematic Generalization? 23374-23385 - Aadarsh Sahoo, Rutav Shah, Rameswar Panda, Kate Saenko, Abir Das:
Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing. 23386-23400 - Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk:
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization. 23401-23412 - Maximilian Thiessen, Thomas Gärtner:
Active Learning of Convex Halfspaces on Graphs. 23413-23425 - Yuhang Li, Yufei Guo, Shanghang Zhang, Shikuang Deng, Yongqing Hai, Shi Gu:
Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks. 23426-23439 - Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy:
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs. 23440-23451 - Onur Teymur, Christopher N. Foley, Philip G. Breen, Toni Karvonen, Chris J. Oates:
Black Box Probabilistic Numerics. 23452-23464 - Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang:
Interpolation can hurt robust generalization even when there is no noise. 23465-23477 - Yilan Chen, Wei Huang, Lam M. Nguyen, Tsui-Wei Weng:
On the Equivalence between Neural Network and Support Vector Machine. 23478-23490 - Shobha Vasudevan, Wenjie Jiang, David Bieber, Rishabh Singh, Hamid Shojaei, Richard Ho, Charles Sutton:
Learning Semantic Representations to Verify Hardware Designs. 23491-23504 - Minguk Kang, Woohyeon Shim, Minsu Cho, Jaesik Park:
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training. 23505-23518 - Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang:
Towards a Theoretical Framework of Out-of-Distribution Generalization. 23519-23531 - David M. Zoltowski, Diana Cai, Ryan P. Adams:
Slice Sampling Reparameterization Gradients. 23532-23544 - Ming-Kun Xie, Sheng-Jun Huang:
Multi-Label Learning with Pairwise Relevance Ordering. 23545-23556 - Xingchao Liu, Xin Tong, Qiang Liu:
Sampling with Trusthworthy Constraints: A Variational Gradient Framework. 23557-23568 - Elias Ramzi, Nicolas Thome, Clément Rambour, Nicolas Audebert, Xavier Bitot:
Robust and Decomposable Average Precision for Image Retrieval. 23569-23581 - El Mehdi Saad, Gilles Blanchard:
Fast rates for prediction with limited expert advice. 23582-23591 - Binh Tang, David S. Matteson:
Probabilistic Transformer For Time Series Analysis. 23592-23608 - Yi Ma, Xiaotian Hao, Jianye Hao, Jiawen Lu, Xing Liu, Xialiang Tong, Mingxuan Yuan, Zhigang Li, Jie Tang, Zhaopeng Meng:
A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems. 23609-23620 - Oliver Hamelijnck, William J. Wilkinson, Niki A. Loppi, Arno Solin, Theodoros Damoulas:
Spatio-Temporal Variational Gaussian Processes. 23621-23633 - Rowan Zellers, Ximing Lu, Jack Hessel, Youngjae Yu, Jae Sung Park, Jize Cao, Ali Farhadi, Yejin Choi:
MERLOT: Multimodal Neural Script Knowledge Models. 23634-23651 - Mohamad Amin Sharifi Kolarijani, G. F. Max, Peyman Mohajerin Esfahani:
Fast Approximate Dynamic Programming for Infinite-Horizon Markov Decision Processes. 23652-23663 - Marvin Zhang, Henrik Marklund, Nikita Dhawan, Abhishek Gupta, Sergey Levine, Chelsea Finn:
Adaptive Risk Minimization: Learning to Adapt to Domain Shift. 23664-23678 - Zeyu Zheng, Vivek Veeriah, Risto Vuorio, Richard L. Lewis, Satinder Singh:
Learning State Representations from Random Deep Action-conditional Predictions. 23679-23691 - Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Mixability made efficient: Fast online multiclass logistic regression. 23692-23702 - Jathushan Rajasegaran, Georgios Pavlakos, Angjoo Kanazawa, Jitendra Malik:
Tracking People with 3D Representations. 23703-23713 - Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli:
Off-Policy Risk Assessment in Contextual Bandits. 23714-23726 - Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro, Peter A. Crozier, Carlos Fernandez-Granda, Eero P. Simoncelli:
Adaptive Denoising via GainTuning. 23727-23740 - Shuli Jiang, Hai Pham, David P. Woodruff, Qiuyi (Richard) Zhang:
Optimal Sketching for Trace Estimation. 23741-23753 - Zhaozhi Qian, Alicia Curth, Mihaela van der Schaar:
Estimating Multi-cause Treatment Effects via Single-cause Perturbation. 23754-23767 - Xiao Wang, Hongrui Liu, Chuan Shi, Cheng Yang:
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration. 23768-23779 - Samuel Gruffaz, Pierre-Emmanuel Poulet, Etienne Maheux, Bruno Jedynak, Stanley Durrleman:
Learning Riemannian metric for disease progression modeling. 23780-23792 - Arthur Prat-Carrabin, Michael Woodford:
Bias and variance of the Bayesian-mean decoder. 23793-23805 - Trent Kyono, Yao Zhang, Alexis Bellot, Mihaela van der Schaar:
MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms. 23806-23817 - Yahui Liu, Enver Sangineto, Wei Bi, Nicu Sebe, Bruno Lepri, Marco De Nadai:
Efficient Training of Visual Transformers with Small Datasets. 23818-23830 - Dominik Stöger, Mahdi Soltanolkotabi
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction. 23831-23843 - Olivier Beaumont, Lionel Eyraud-Dubois, Alena Shilova:
Efficient Combination of Rematerialization and Offloading for Training DNNs. 23844-23857 - Raghav Kansal, Javier M. Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopulos:
Particle Cloud Generation with Message Passing Generative Adversarial Networks. 23858-23871 - Hao Yu, Fu Li, Mahdi Saleh, Benjamin Busam, Slobodan Ilic:
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust PointCloud Registration. 23872-23884 - Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Tizian Thieringer, Matthias Bethge, Felix A. Wichmann, Wieland Brendel:
Partial success in closing the gap between human and machine vision. 23885-23899 - Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham M. Kakade, Ali Farhadi:
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes. 23900-23913 - Sidak Pal Singh, Gregor Bachmann, Thomas Hofmann:
Analytic Insights into Structure and Rank of Neural Network Hessian Maps. 23914-23927 - Arlind Kadra, Marius Lindauer, Frank Hutter, Josif Grabocka:
Well-tuned Simple Nets Excel on Tabular Datasets. 23928-23941 - Duong H. Le, Khoi D. Nguyen, Khoi Nguyen, Quoc-Huy Tran, Rang Nguyen, Binh-Son Hua:
POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples. 23942-23955 - Yihan Du, Yuko Kuroki, Wei Chen:
Combinatorial Pure Exploration with Bottleneck Reward Function. 23956-23967 - Matej Grcic, Ivan Grubisic, Sinisa Segvic
Densely connected normalizing flows. 23968-23982 - Charlie Blake, Vitaly Kurin, Maximilian Igl, Shimon Whiteson:
Snowflake: Scaling GNNs to high-dimensional continuous control via parameter freezing. 23983-23992 - Brian Hu Zhang, Tuomas Sandholm:
Subgame solving without common knowledge. 23993-24004 - Safwan Hossain, Evi Micha, Nisarg Shah:
Fair Algorithms for Multi-Agent Multi-Armed Bandits. 24005-24017 - Thomy Phan, Fabian Ritz, Lenz Belzner, Philipp Altmann, Thomas Gabor, Claudia Linnhoff-Popien:
VAST: Value Function Factorization with Variable Agent Sub-Teams. 24018-24032 - Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar:
On the Stochastic Stability of Deep Markov Models. 24033-24047 - Gaurav Gupta, Xiongye Xiao, Paul Bogdan:
Multiwavelet-based Operator Learning for Differential Equations. 24048-24062 - Aakash Kaku, Sahana Upadhya, Narges Razavian:
Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning. 24063-24074 - Xin Liu, Bin Li, Pengyi Shi, Lei Ying:
An Efficient Pessimistic-Optimistic Algorithm for Stochastic Linear Bandits with General Constraints. 24075-24086 - Sitan Chen, Adam R. Klivans, Raghu Meka:
Efficiently Learning One Hidden Layer ReLU Networks From Queries. 24087-24098 - Magnus Ross, Michael T. Smith, Mauricio A. Álvarez:
Learning Nonparametric Volterra Kernels with Gaussian Processes. 24099-24110 - Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause:
DiBS: Differentiable Bayesian Structure Learning. 24111-24123 - Michaël Fanuel, Rémi Bardenet:
Nonparametric estimation of continuous DPPs with kernel methods. 24124-24136 - Taehyeon Kim, Jongwoo Ko, Sangwook Cho, Jinhwan Choi, Se-Young Yun:
FINE Samples for Learning with Noisy Labels. 24137-24149 - Sadamori Kojaku, Jisung Yoon, Isabel Constantino, Yong-Yeol Ahn:
Residual2Vec: Debiasing graph embedding with random graphs. 24150-24163 - Ke Wang, Vidya Muthukumar, Christos Thrampoulidis:
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation. 24164-24179 - François Bachoc, Tommaso Cesari, Sébastien Gerchinovitz:
Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates. 24180-24192 - Yi-Lin Sung, Varun Nair, Colin Raffel:
Training Neural Networks with Fixed Sparse Masks. 24193-24205 - Hassan Akbari, Liangzhe Yuan, Rui Qian, Wei-Hong Chuang, Shih-Fu Chang, Yin Cui, Boqing Gong:
VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text. 24206-24221 - Hao Wang, Yizhe Huang, Rui Gao, Flávio P. Calmon:
Analyzing the Generalization Capability of SGLD Using Properties of Gaussian Channels. 24222-24234 - Antonia Chmiela, Elias B. Khalil, Ambros M. Gleixner, Andrea Lodi, Sebastian Pokutta:
Learning to Schedule Heuristics in Branch and Bound. 24235-24246 - Zhengyang Geng, Xin-Yu Zhang, Shaojie Bai, Yisen Wang, Zhouchen Lin:
On Training Implicit Models. 24247-24260 - Ilya O. Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy:
MLP-Mixer: An all-MLP Architecture for Vision. 24261-24272 - Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc:
A Framework to Learn with Interpretation. 24273-24285 - Jiun Tian Hoe, Kam Woh Ng, Tianyu Zhang, Chee Seng Chan, Yi-Zhe Song, Tao Xiang:
One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective. 24286-24298 - Linjian Ma, Edgar Solomonik:
Fast and accurate randomized algorithms for low-rank tensor decompositions. 24299-24312 - Artin Spiridonoff, Alex Olshevsky, Yannis Paschalidis:
Communication-efficient SGD: From Local SGD to One-Shot Averaging. 24313-24326 - John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard E. Turner:
Memory Efficient Meta-Learning with Large Images. 24327-24339 - Emmanuel Abbe, Pritish Kamath, Eran Malach, Colin Sandon, Nathan Srebro:
On the Power of Differentiable Learning versus PAC and SQ Learning. 24340-24351 - William T. Stephenson, Zachary Frangella, Madeleine Udell, Tamara Broderick:
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression. 24352-24364 - Jihun Yun, Aurélie C. Lozano, Eunho Yang:
Adaptive Proximal Gradient Methods for Structured Neural Networks. 24365-24378 - Russell Mendonca, Oleh Rybkin, Kostas Daniilidis, Danijar Hafner, Deepak Pathak:
Discovering and Achieving Goals via World Models. 24379-24391 - Yingbin Bai, Erkun Yang, Bo Han, Yanhua Yang, Jiatong Li, Yinian Mao, Gang Niu, Tongliang Liu:
Understanding and Improving Early Stopping for Learning with Noisy Labels. 24392-24403 - Mohammad Ali Bashiri, Brian D. Ziebart, Xinhua Zhang:
Distributionally Robust Imitation Learning. 24404-24417 - Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis:
On the Power of Edge Independent Graph Models. 24418-24429 - Reda Ouhamma, Odalric-Ambrym Maillard, Vianney Perchet:
Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge. 24430-24441 - Romain Laroche, Remi Tachet des Combes:
Dr Jekyll & Mr Hyde: the strange case of off-policy policy updates. 24442-24454 - Menoua Keshishian, Samuel Norman-Haignere, Nima Mesgarani:
Understanding Adaptive, Multiscale Temporal Integration In Deep Speech Recognition Systems. 24455-24467 - Zineng Tang, Jaemin Cho, Hao Tan, Mohit Bansal:
VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer. 24468-24481 - Reid McIlroy-Young, Yu Wang, Siddhartha Sen, Jon M. Kleinberg, Ashton Anderson:
Detecting Individual Decision-Making Style: Exploring Behavioral Stylometry in Chess. 24482-24497 - Zhe Dong, Andriy Mnih, George Tucker:
Coupled Gradient Estimators for Discrete Latent Variables. 24498-24508 - Zhili Wang, Shimin Di, Lei Chen:
AutoGEL: An Automated Graph Neural Network with Explicit Link Information. 24509-24522 - Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
RL for Latent MDPs: Regret Guarantees and a Lower Bound. 24523-24534 - Shubhanshu Shekhar, Greg Fields, Mohammad Ghavamzadeh, Tara Javidi
Adaptive Sampling for Minimax Fair Classification. 24535-24544 - Anup Sarma, Sonali Singh, Huaipan Jiang, Rui Zhang, Mahmut T. Kandemir, Chita R. Das:
Structured in Space, Randomized in Time: Leveraging Dropout in RNNs for Efficient Training. 24545-24555 - Qiang Zhang, Jinyuan Fang, Zaiqiao Meng, Shangsong Liang, Emine Yilmaz:
Variational Continual Bayesian Meta-Learning. 24556-24568 - Xinyang Jiang, Lu Liu, Caihua Shan, Yifei Shen, Xuanyi Dong, Dongsheng Li:
Recognizing Vector Graphics without Rasterization. 24569-24580 - Steinar Laenen, Luca Bertinetto:
On Episodes, Prototypical Networks, and Few-Shot Learning. 24581-24592 - Wei-Ning Chen, Peter Kairouz, Ayfer Özgür:
Pointwise Bounds for Distribution Estimation under Communication Constraints. 24593-24603 - Yang Sui, Miao Yin, Yi Xie, Huy Phan, Saman A. Zonouz, Bo Yuan:
CHIP: CHannel Independence-based Pruning for Compact Neural Networks. 24604-24616 - Sangjoon Park, Gwanghyun Kim, Jeongsol Kim, Boah Kim, Jong Chul Ye:
Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis. 24617-24630 - Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas:
Active Offline Policy Selection. 24631-24644 - Hee Min Choi, Hyoa Kang, Dokwan Oh:
Unsupervised Representation Transfer for Small Networks: I Believe I Can Distill On-the-Fly. 24645-24658 - Houshuang Chen, Zengfeng Huang
Understanding Bandits with Graph Feedback. 24659-24669 - Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan:
Information-theoretic generalization bounds for black-box learning algorithms. 24670-24682 - Qiming Hu, Xiaojie Guo:
Trash or Treasure? An Interactive Dual-Stream Strategy for Single Image Reflection Separation. 24683-24694 - Tengwei Song, Jie Luo, Lei Huang:
Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding. 24695-24706 - Marco Bagatella, Miroslav Olsák, Michal Rolínek, Georg Martius:
Planning from Pixels in Environments with Combinatorially Hard Search Spaces. 24707-24718 - Babhru Joshi, Xiaowei Li, Yaniv Plan, Özgür Yilmaz:
PLUGIn: A simple algorithm for inverting generative models with recovery guarantees. 24719-24729 - Pablo Moreno-Muñoz, Antonio Artés-Rodríguez, Mauricio A. Álvarez:
Modular Gaussian Processes for Transfer Learning. 24730-24740 - Youngjoong Kwon, Dahun Kim, Duygu Ceylan, Henry Fuchs:
Neural Human Performer: Learning Generalizable Radiance Fields for Human Performance Rendering. 24741-24752 - Cristina Butucea, Yann Issartel:
Locally differentially private estimation of functionals of discrete distributions. 24753-24764 - Jacob A. Zavatone-Veth, Abdulkadir Canatar, Benjamin S. Ruben, Cengiz Pehlevan:
Asymptotics of representation learning in finite Bayesian neural networks. 24765-24777 - Hang Wang, Sen Lin, Junshan Zhang:
Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error Feedback. 24778-24790 - Petar Stojanov, Zijian Li, Mingming Gong, Ruichu Cai, Jaime G. Carbonell, Kun Zhang:
Domain Adaptation with Invariant Representation Learning: What Transformations to Learn? 24791-24803 - Yusuke Tashiro, Jiaming Song, Yang Song, Stefano Ermon:
CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation. 24804-24816 - Yangyi Lu, Amirhossein Meisami, Ambuj Tewari:
Causal Bandits with Unknown Graph Structure. 24817-24828 - Jakub Tarnawski, Deepak Narayanan, Amar Phanishayee:
Piper: Multidimensional Planner for DNN Parallelization. 24829-24840 - Jean Kaddour, Yuchen Zhu, Qi Liu, Matt J. Kusner, Ricardo Silva:
Causal Effect Inference for Structured Treatments. 24841-24854 - Ali Hashemi, Yijing Gao, Chang Cai, Sanjay Ghosh, Klaus-Robert Müller, Srikantan S. Nagarajan, Stefan Haufe:
Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging. 24855-24870 - Sebastian Zeng, Florian Graf, Christoph D. Hofer, Roland Kwitt:
Topological Attention for Time Series Forecasting. 24871-24882 - Stefani Karp, Ezra Winston, Yuanzhi Li, Aarti Singh:
Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels. 24883-24897 - Bowen Pan, Rameswar Panda, Yifan Jiang, Zhangyang Wang, Rogério Feris, Aude Oliva:
IA-RED$^2$: Interpretability-Aware Redundancy Reduction for Vision Transformers. 24898-24911 - T. Nathan Mundhenk, Mikel Landajuela, Ruben Glatt, Cláudio P. Santiago, Daniel M. Faissol, Brenden K. Petersen:
Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding. 24912-24923 - Shuhao Cao:
Choose a Transformer: Fourier or Galerkin. 24924-24940 - Zhiting Hu, Li Erran Li:
A Causal Lens for Controllable Text Generation. 24941-24955 - Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer:
Differentially Private Multi-Armed Bandits in the Shuffle Model. 24956-24967 - Lijun Zhang, Guanghui Wang, Wei-Wei Tu, Wei Jiang, Zhi-Hua Zhou:
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions. 24968-24980 - James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck:
Learning Hard Optimization Problems: A Data Generation Perspective. 24981-24992 - Weiwei Sun, Andrea Tagliasacchi, Boyang Deng, Sara Sabour, Soroosh Yazdani, Geoffrey E. Hinton, Kwang Moo Yi:
Canonical Capsules: Self-Supervised Capsules in Canonical Pose. 24993-25005 - Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer:
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. 25006-25018 - Zhengyi Luo, Ryo Hachiuma, Ye Yuan, Kris Kitani:
Dynamics-regulated kinematic policy for egocentric pose estimation. 25019-25032 - Idan Amir, Yair Carmon, Tomer Koren, Roi Livni:
Never Go Full Batch (in Stochastic Convex Optimization). 25033-25043 - El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui
Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning). 25044-25057 - Heng Chang, Yu Rong, Tingyang Xu, Yatao Bian, Shiji Zhou, Xin Wang, Junzhou Huang, Wenwu Zhu:
Not All Low-Pass Filters are Robust in Graph Convolutional Networks. 25058-25071 - Xinyi Wang, Wenhu Chen, Michael Saxon, William Yang Wang:
Counterfactual Maximum Likelihood Estimation for Training Deep Networks. 25072-25085 - Xian Li, Hongyu Gong:
Robust Optimization for Multilingual Translation with Imbalanced Data. 25086-25099 - Yoan Russac, Christina Katsimerou, Dennis Bohle, Olivier Cappé, Aurélien Garivier, Wouter M. Koolen:
A/B/n Testing with Control in the Presence of Subpopulations. 25100-25110 - Giora Simchoni, Saharon Rosset:
Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks. 25111-25122 - Jungsoo Lee, Eungyeup Kim, Juyoung Lee, Jihyeon Lee, Jaegul Choo:
Learning Debiased Representation via Disentangled Feature Augmentation. 25123-25133 - Jiani Huang, Ziyang Li, Binghong Chen, Karan Samel, Mayur Naik, Le Song, Xujie Si:
Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning. 25134-25145 - Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, Joseph J. Lim:
Learning to Synthesize Programs as Interpretable and Generalizable Policies. 25146-25163 - Shahab Bakhtiari, Patrick J. Mineault, Timothy P. Lillicrap, Christopher C. Pack, Blake A. Richards:
The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning. 25164-25178 - Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y. Zou:
Adversarial Training Helps Transfer Learning via Better Representations. 25179-25191 - Maxwell I. Nye, Michael Henry Tessler, Joshua B. Tenenbaum, Brenden M. Lake:
Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning. 25192-25204 - Giovanni S. Alberti, Ernesto De Vito, Matti Lassas, Luca Ratti, Matteo Santacesaria:
Learning the optimal Tikhonov regularizer for inverse problems. 25205-25216 - Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian:
NovelD: A Simple yet Effective Exploration Criterion. 25217-25230 - Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice:
On Margin-Based Cluster Recovery with Oracle Queries. 25231-25243 - Vignesh Ram Somnath, Charlotte Bunne, Andreas Krause:
Multi-Scale Representation Learning on Proteins. 25244-25255 - Florian Bernard, Daniel Cremers, Johan Thunberg:
Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation. 25256-25266 - Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou:
Second-Order Neural ODE Optimizer. 25267-25279 - Pablo Barceló, Floris Geerts, Juan L. Reutter, Maksimilian Ryschkov:
Graph Neural Networks with Local Graph Parameters. 25280-25293 - Tianyi Chen, Yuejiao Sun, Wotao Yin:
Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems. 25294-25307 - Nikita Araslanov, Simone Schaub-Meyer, Stefan Roth:
Dense Unsupervised Learning for Video Segmentation. 25308-25319 - Elia Turner, Kabir V. Dabholkar, Omri Barak:
Charting and Navigating the Space of Solutions for Recurrent Neural Networks. 25320-25333 - Hongchang Gao, Heng Huang:
Fast Training Method for Stochastic Compositional Optimization Problems. 25334-25345 - Mingyuan Mao, Peng Gao, Renrui Zhang, Honghui Zheng, Teli Ma, Yan Peng, Errui Ding, Baochang Zhang, Shumin Han:
Dual-stream Network for Visual Recognition. 25346-25358 - Chenlin Meng, Yang Song, Wenzhe Li, Stefano Ermon:
Estimating High Order Gradients of the Data Distribution by Denoising. 25359-25369 - Sihang Guo, Ruohan Zhang, Bo Liu, Yifeng Zhu, Dana H. Ballard, Mary M. Hayhoe, Peter Stone:
Machine versus Human Attention in Deep Reinforcement Learning Tasks. 25370-25385 - Jai Moondra, Hassan Mortagy, Swati Gupta:
Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes. 25386-25399 - Sara Sangalli, Ertunc Erdil, Andreas M. Hötker, Olivio Donati, Ender Konukoglu:
Constrained Optimization to Train Neural Networks on Critical and Under-Represented Classes. 25400-25411 - Marcin Tomczak, Siddharth Swaroop, Andrew Y. K. Foong, Richard E. Turner:
Collapsed Variational Bounds for Bayesian Neural Networks. 25412-25426 - Tommaso d'Orsi, Chih-Hung Liu, Rajai Nasser, Gleb Novikov, David Steurer
Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers. 25427-25438 - Runzhe Wu, Yufeng Zhang, Zhuoran Yang, Zhaoran Wang:
Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration. 25439-25451 - Lifeng Zhang:
Absolute Neighbour Difference based Correlation Test for Detecting Heteroscedastic Relationships. 25452-25462 - Shibo Li, Robert M. Kirby, Shandian Zhe:
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks. 25463-25475 - Weirui Ye, Shaohuai Liu, Thanard Kurutach, Pieter Abbeel, Yang Gao:
Mastering Atari Games with Limited Data. 25476-25488 - Clémence Réda, Andrea Tirinzoni, Rémy Degenne:
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification. 25489-25501 - Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine:
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability. 25502-25515 - Konpat Preechakul, Chawan Piansaddhayanon, Burin Naowarat, Tirasan Khandhawit, Sira Sriswasdi, Ekapol Chuangsuwanich:
Set Prediction in the Latent Space. 25516-25527 - Yixin Chen, Tonmoy Dey, Alan Kuhnle:
Best of Both Worlds: Practical and Theoretically Optimal Submodular Maximization in Parallel. 25528-25539 - Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft:
Fine-grained Generalization Analysis of Inductive Matrix Completion. 25540-25552 - Yixing Xu, Kai Han, Chang Xu, Yehui Tang, Chunjing Xu, Yunhe Wang:
Learning Frequency Domain Approximation for Binary Neural Networks. 25553-25565 - Alec Kerrigan, Kevin Duarte, Yogesh S. Rawat, Mubarak Shah:
Reformulating Zero-shot Action Recognition for Multi-label Actions. 25566-25577 - Shubhada Agrawal, Wouter M. Koolen, Sandeep Juneja:
Optimal Best-Arm Identification Methods for Tail-Risk Measures. 25578-25590 - Irina Higgins, Peter Wirnsberger, Andrew Jaegle, Aleksandar Botev:
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision. 25591-25605 - Ashwinkumar Ganesan, Hang Gao, Sunil Gandhi, Edward Raff, Tim Oates, James Holt, Mark McLean:
Learning with Holographic Reduced Representations. 25606-25620 - Yuping Luo, Tengyu Ma:
Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations. 25621-25632 - Aurélien Lucchi, Antonio Orvieto, Adamos Solomou:
On the Second-order Convergence Properties of Random Search Methods. 25633-25645 - Hidenori Tanaka, Daniel Kunin:
Noether's Learning Dynamics: Role of Symmetry Breaking in Neural Networks. 25646-25660 - Dror Freirich, Tomer Michaeli, Ron Meir:
A Theory of the Distortion-Perception Tradeoff in Wasserstein Space. 25661-25672 - Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio:
Neural Production Systems. 25673-25687 - Mher Safaryan, Filip Hanzely, Peter Richtárik:
Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization. 25688-25702 - Vladimir A. Ivanov, Konstantinos P. Michmizos:
Increasing Liquid State Machine Performance with Edge-of-Chaos Dynamics Organized by Astrocyte-modulated Plasticity. 25703-25719 - Bailey Flanigan, Gregory Kehne, Ariel D. Procaccia:
Fair Sortition Made Transparent. 25720-25731 - Seungyul Han, Youngchul Sung:
A Max-Min Entropy Framework for Reinforcement Learning. 25732-25745 - Tom Zahavy, Brendan O'Donoghue, Guillaume Desjardins, Satinder Singh:
Reward is enough for convex MDPs. 25746-25759 - Shahrzad Haddadan, Yue Zhuang, Cyrus Cousins, Eli Upfal:
Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds. 25760-25772 - Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin, Yuekai Sun:
Does enforcing fairness mitigate biases caused by subpopulation shift? 25773-25784 - Desi R. Ivanova, Adam Foster, Steven Kleinegesse, Michael U. Gutmann, Thomas Rainforth:
Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods. 25785-25798 - Yu Bai, Chi Jin, Huan Wang, Caiming Xiong:
Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games. 25799-25811 - Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, Hiroyuki Toda:
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm. 25812-25823 - Mao Li, Kaiqi Jiang, Xinhua Zhang:
Implicit Task-Driven Probability Discrepancy Measure for Unsupervised Domain Adaptation. 25824-25838 - Ziming Zhang, Yun Yue, Guojun Wu, Yanhua Li, Haichong K. Zhang:
SBO-RNN: Reformulating Recurrent Neural Networks via Stochastic Bilevel Optimization. 25839-25851 - Aymen Al Marjani, Aurélien Garivier, Alexandre Proutière:
Navigating to the Best Policy in Markov Decision Processes. 25852-25864 - Wenhan Xian, Feihu Huang, Yanfu Zhang, Heng Huang:
A Faster Decentralized Algorithm for Nonconvex Minimax Problems. 25865-25877 - Qi Chen, Changjian Shui, Mario Marchand:
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis. 25878-25890 - Ilias Diakonikolas, Jongho Park, Christos Tzamos:
ReLU Regression with Massart Noise. 25891-25903 - Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier:
Identification of the Generalized Condorcet Winner in Multi-dueling Bandits. 25904-25916 - Luca Viano, Yu-Ting Huang, Parameswaran Kamalaruban, Adrian Weller, Volkan Cevher
Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch. 25917-25931 - Xi Shen, Yang Xiao, Shell Xu Hu, Othman Sbai, Mathieu Aubry:
Re-ranking for image retrieval and transductive few-shot classification. 25932-25943 - Felix Petersen, Debarghya Mukherjee, Yuekai Sun, Mikhail Yurochkin:
Post-processing for Individual Fairness. 25944-25955 - Kuniaki Saito, Donghyun Kim, Kate Saenko:
OpenMatch: Open-Set Semi-supervised Learning with Open-set Consistency Regularization. 25956-25967 - Devendra Singh Sachan, Siva Reddy, William L. Hamilton, Chris Dyer, Dani Yogatama:
End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering. 25968-25981 - Bahram Behzadian, Marek Petrik, Chin Pang Ho:
Fast Algorithms for $L_\infty$-constrained S-rectangular Robust MDPs. 25982-25992 - Ziyue Huang, Yuting Liang, Ke Yi:
Instance-optimal Mean Estimation Under Differential Privacy. 25993-26004 - Thomas Fel, Rémi Cadène, Mathieu Chalvidal, Matthieu Cord, David Vigouroux, Thomas Serre:
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis. 26005-26014 - Kamal Gupta, Gowthami Somepalli, Anubhav Gupta, Vinoj Yasanga Jayasundara Magalle Hewa, Matthias Zwicker, Abhinav Shrivastava:
PatchGame: Learning to Signal Mid-level Patches in Referential Games. 26015-26027 - Tim Janke, Mohamed Ghanmi, Florian Steinke:
Implicit Generative Copulas. 26028-26039 - Yi Ren, Donald Goldfarb:
Tensor Normal Training for Deep Learning Models. 26040-26052 - Reilly Raab, Yang Liu:
Unintended Selection: Persistent Qualification Rate Disparities and Interventions. 26053-26065 - Boyang Deng, Charles R. Qi, Mahyar Najibi, Thomas A. Funkhouser, Yin Zhou, Dragomir Anguelov:
Revisiting 3D Object Detection From an Egocentric Perspective. 26066-26079 - Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu:
Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD. 26080-26090 - Sen Cui, Weishen Pan, Jian Liang, Changshui Zhang, Fei Wang:
Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning. 26091-26102 - Xinyi Tong, Xiangxiang Xu, Shao-Lun Huang, Lizhong Zheng:
A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning. 26103-26116 - Dantong Niu, Ruohao Guo, Yisen Wang:
Morié Attack (MA): A New Potential Risk of Screen Photos. 26117-26129 - Hideaki Kim:
Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation. 26130-26142 - Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo:
Lattice partition recovery with dyadic CART. 26143-26155 - Tuomas P. Oikarinen, Wang Zhang, Alexandre Megretski, Luca Daniel, Tsui-Wei Weng:
Robust Deep Reinforcement Learning through Adversarial Loss. 26156-26167 - Kefan Dong, Jiaqi Yang, Tengyu Ma:
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature. 26168-26182 - Yuxin Fang, Bencheng Liao, Xinggang Wang, Jiemin Fang, Jiyang Qi, Rui Wu, Jianwei Niu, Wenyu Liu:
You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection. 26183-26197 - Sirui Li, Zhongxia Yan, Cathy Wu:
Learning to delegate for large-scale vehicle routing. 26198-26211 - Weisen Jiang, James T. Kwok, Yu Zhang:
Effective Meta-Regularization by Kernelized Proximal Regularization. 26212-26222 - Charles Jin, Martin C. Rinard:
Towards Context-Agnostic Learning Using Synthetic Data. 26223-26236 - Jeffrey Negrea, Blair L. Bilodeau, Nicolò Campolongo, Francesco Orabona, Daniel M. Roy:
Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers. 26237-26249 - Yu Shen, Laura Y. Zheng, Manli Shu, Weizi Li, Tom Goldstein, Ming C. Lin:
Gradient-Free Adversarial Training Against Image Corruption for Learning-based Steering. 26250-26263 - Liyuan Xu, Heishiro Kanagawa, Arthur Gretton:
Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation. 26264-26275 - Anna P. Meyer, Aws Albarghouthi, Loris D'Antoni:
Certifying Robustness to Programmable Data Bias in Decision Trees. 26276-26288 - Benjamin Attal, Eliot Laidlaw, Aaron Gokaslan, Changil Kim, Christian Richardt, James Tompkin, Matthew O'Toole:
TöRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesis. 26289-26301 - Yoon Kim:
Sequence-to-Sequence Learning with Latent Neural Grammars. 26302-26317 - Stefanos Leonardos, Georgios Piliouras, Kelly Spendlove:
Exploration-Exploitation in Multi-Agent Competition: Convergence with Bounded Rationality. 26318-26331 - Atara Kaplan, Dan Garber:
Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems. 26332-26344 - Kate Rakelly, Abhishek Gupta, Carlos Florensa, Sergey Levine:
Which Mutual-Information Representation Learning Objectives are Sufficient for Control? 26345-26357 - Junjiao Tian, Dylan Yung, Yen-Chang Hsu, Zsolt Kira:
A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition. 26358-26369 - Mahdi Haghifam, Gintare Karolina Dziugaite, Shay Moran, Daniel M. Roy:
Towards a Unified Information-Theoretic Framework for Generalization. 26370-26381 - Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel J. Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire:
Bayesian decision-making under misspecified priors with applications to meta-learning. 26382-26394 - Rajat Talak, Siyi Hu, Lisa Peng, Luca Carlone:
Neural Trees for Learning on Graphs. 26395-26408 - Pranav Subramani, Nicholas Vadivelu, Gautam Kamath:
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization. 26409-26421 - Giang Nguyen, Daeyoung Kim, Anh Nguyen:
The effectiveness of feature attribution methods and its correlation with automatic evaluation scores. 26422-26436 - Zifan Wu, Chao Yu, Deheng Ye, Junge Zhang, Haiyin Piao, Hankz Hankui Zhuo:
Coordinated Proximal Policy Optimization. 26437-26448 - Youngkyu Hong, Eunho Yang:
Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning. 26449-26461 - Weijiang Yu, Haoteng Zheng, Mengfei Li, Lei Ji, Lijun Wu, Nong Xiao, Nan Duan:
Learning from Inside: Self-driven Siamese Sampling and Reasoning for Video Question Answering. 26462-26474 - Ryusei Shingaki, Manabu Kuroki:
Identification and Estimation of Joint Probabilities of Potential Outcomes in Observational Studies with Covariate Information. 26475-26486 - Quentin Rebjock, Baris Kurt, Tim Januschowski, Laurent Callot:
Online false discovery rate control for anomaly detection in time series. 26487-26498 - Siddharth Reddy, Anca D. Dragan, Sergey Levine:
Pragmatic Image Compression for Human-in-the-Loop Decision-Making. 26499-26510 - Yuxuan Han, Zhipeng Liang, Yang Wang, Jiheng Zhang:
Generalized Linear Bandits with Local Differential Privacy. 26511-26522 - Yue Xing, Qifan Song, Guang Cheng:
On the Algorithmic Stability of Adversarial Training. 26523-26535 - Stefan O'Toole, Nir Lipovetzky, Miquel Ramírez, Adrian R. Pearce:
Width-based Lookaheads with Learnt Base Policies and Heuristics Over the Atari-2600 Benchmark. 26536-26547 - Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney:
Characterizing possible failure modes in physics-informed neural networks. 26548-26560 - Haibo Chen, Lei Zhao, Zhizhong Wang, Huiming Zhang, Zhiwen Zuo, Ailin Li, Wei Xing, Dongming Lu:
Artistic Style Transfer with Internal-external Learning and Contrastive Learning. 26561-26573 - Yu-Xuan Huang, Wang-Zhou Dai, Le-Wen Cai, Stephen H. Muggleton, Yuan Jiang:
Fast Abductive Learning by Similarity-based Consistency Optimization. 26574-26584 - Thomas Scialom, Paul-Alexis Dray, Jacopo Staiano, Sylvain Lamprier, Benjamin Piwowarski:
To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs. 26585-26597 - Indra Kumar, Carlos Scheidegger, Suresh Venkatasubramanian, Sorelle A. Friedler:
Shapley Residuals: Quantifying the limits of the Shapley value for explanations. 26598-26608 - Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Jingjing Liu, Zhangyang Wang:
The Elastic Lottery Ticket Hypothesis. 26609-26621 - Kishan K. C., Rui Li, Mahdi Gilany:
Joint Inference for Neural Network Depth and Dropout Regularization. 26622-26634 - Brendan Leigh Ross, Jesse C. Cresswell:
Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows. 26635-26648 - Quinlan Dawkins, Minbiao Han, Haifeng Xu:
The Limits of Optimal Pricing in the Dark. 26649-26660 - Meera Hahn, Devendra Singh Chaplot, Shubham Tulsiani, Mustafa Mukadam, James M. Rehg, Abhinav Gupta:
No RL, No Simulation: Learning to Navigate without Navigating. 26661-26673 - Jiangning Zhang, Chao Xu, Jian Li, Wenzhou Chen, Yabiao Wang, Ying Tai, Shuo Chen, Chengjie Wang, Feiyue Huang, Yong Liu:
Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model. 26674-26688 - Mike Wu, Noah D. Goodman, Stefano Ermon:
Improving Compositionality of Neural Networks by Decoding Representations to Inputs. 26689-26700 - Fang Kong, Yueran Yang, Wei Chen, Shuai Li:
The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle. 26701-26713 - Zhuo Huang, Chao Xue, Bo Han, Jian Yang, Chen Gong:
Universal Semi-Supervised Learning. 26714-26725 - Aya Abdelsalam Ismail, Héctor Corrada Bravo, Soheil Feizi:
Improving Deep Learning Interpretability by Saliency Guided Training. 26726-26739 - Alicia Curth, Changhee Lee, Mihaela van der Schaar:
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data. 26740-26753 - Jayadev Acharya, Clément L. Canonne, Aditya Vikram Singh, Himanshu Tyagi:
Optimal Rates for Nonparametric Density Estimation under Communication Constraints. 26754-26766 - Lijun Ding, Liwei Jiang, Yudong Chen, Qing Qu, Zhihui Zhu:
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery. 26767-26778 - Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel:
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. 26779-26791 - Guy Lorberbom, Daniel D. Johnson, Chris J. Maddison, Daniel Tarlow, Tamir Hazan:
Learning Generalized Gumbel-max Causal Mechanisms. 26792-26803 - Wei Tang, Chien-Ju Ho, Yang Liu:
Bandit Learning with Delayed Impact of Actions. 26804-26817 - Brian Bullins, Kumar Kshitij Patel, Ohad Shamir, Nathan Srebro, Blake E. Woodworth:
A Stochastic Newton Algorithm for Distributed Convex Optimization. 26818-26830 - Yutong Bai, Jieru Mei, Alan L. Yuille, Cihang Xie:
Are Transformers more robust than CNNs? 26831-26843 - Shaojie Li, Yong Liu:
Towards Sharper Generalization Bounds for Structured Prediction. 26844-26857 - Chengyuan Yao, Pavol Bielik, Petar Tsankov, Martin T. Vechev:
Automated Discovery of Adaptive Attacks on Adversarial Defenses. 26858-26870 - Qi Chen, Sourabh Vora, Oscar Beijbom:
PolarStream: Streaming Object Detection and Segmentation with Polar Pillars. 26871-26883 - Zhen Dai, Mina Karzand, Nathan Srebro:
Representation Costs of Linear Neural Networks: Analysis and Design. 26884-26896 - Akash Kumar, Yuxin Chen, Adish Singla:
Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm. 26897-26910 - Yiyue Qian, Yiming Zhang, Yanfang Ye, Chuxu Zhang:
Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media. 26911-26923 - Hong Chen, Yudong Chen, Xin Wang, Ruobing Xie, Rui Wang, Feng Xia, Wenwu Zhu:
Curriculum Disentangled Recommendation with Noisy Multi-feedback. 26924-26936 - Roberto Dessì, Eugene Kharitonov, Marco Baroni:
Interpretable agent communication from scratch (with a generic visual processor emerging on the side). 26937-26949 - Zheng Chang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Yan Ye, Xiang Xinguang, Wen Gao:
MAU: A Motion-Aware Unit for Video Prediction and Beyond. 26950-26962 - Christopher Hoang, Sungryull Sohn, Jongwook Choi, Wilka Carvalho, Honglak Lee:
Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning. 26963-26975 - Yuchen Wu, Jakab Tardos, MohammadHossein Bateni, André Linhares, Filipe Miguel Gonçalves de Almeida, Andrea Montanari, Ashkan Norouzi-Fard:
Streaming Belief Propagation for Community Detection. 26976-26988 - Emmanuel Abbe, Enric Boix-Adserà, Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj:
The staircase property: How hierarchical structure can guide deep learning. 26989-27002 - Xitong Zhang, Yixuan He, Nathan Brugnone, Michael Perlmutter, Matthew J. Hirn:
MagNet: A Neural Network for Directed Graphs. 27003-27015 - Hayeon Lee, Sewoong Lee, Song Chong, Sung Ju Hwang:
Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning. 27016-27028 - Yuzhou Chen, Baris Coskunuzer, Yulia R. Gel:
Topological Relational Learning on Graphs. 27029-27042 - Pascal Mattia Esser, Leena C. Vankadara, Debarghya Ghoshdastidar:
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks. 27043-27056 - Ruiquan Huang, Weiqiang Wu, Jing Yang, Cong Shen:
Federated Linear Contextual Bandits. 27057-27068 - Sijun Tan, Jibang Wu, Xiaohui Bei, Haifeng Xu:
Least Square Calibration for Peer Reviews. 27069-27080 - Thiago Serra, Xin Yu, Abhinav Kumar, Srikumar Ramalingam:
Scaling Up Exact Neural Network Compression by ReLU Stability. 27081-27093 - Thomas A. Langlois, H. Charles Zhao, Erin Grant, Ishita Dasgupta, Thomas L. Griffiths, Nori Jacoby:
Passive attention in artificial neural networks predicts human visual selectivity. 27094-27106 - Longyuan Li, Jian Yao, Li K. Wenliang, Tong He, Tianjun Xiao, Junchi Yan, David Wipf, Zheng Zhang:
GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction. 27107-27118 - Ning Xu, Congyu Qiao, Xin Geng, Min-Ling Zhang:
Instance-Dependent Partial Label Learning. 27119-27130 - Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang:
Deep Learning with Label Differential Privacy. 27131-27145 - Tong Chen, Jean B. Lasserre, Victor Magron, Edouard Pauwels:
Semialgebraic Representation of Monotone Deep Equilibrium Models and Applications to Certification. 27146-27159 - Ruohan Wang, Massimiliano Pontil, Carlo Ciliberto:
The Role of Global Labels in Few-Shot Classification and How to Infer Them. 27160-27170 - Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt
NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction. 27171-27183 - Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan:
Improved Guarantees for Offline Stochastic Matching via new Ordered Contention Resolution Schemes. 27184-27195 - Zhu Zhang, Jianxin Ma, Chang Zhou, Rui Men, Zhikang Li, Ming Ding, Jie Tang, Jingren Zhou, Hongxia Yang:
UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis. 27196-27208 - Tim Seyde, Igor Gilitschenski, Wilko Schwarting, Bartolomeo Stellato, Martin A. Riedmiller, Markus Wulfmeier, Daniela Rus:
Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies. 27209-27221 - Suyoung Lee, Sae-Young Chung:
Improving Generalization in Meta-RL with Imaginary Tasks from Latent Dynamics Mixture. 27222-27235 - Jiefeng Li, Tong Chen, Ruiqi Shi, Yujing Lou, Yong-Lu Li, Cewu Lu:
Localization with Sampling-Argmax. 27236-27248 - Dongyue Li, Hongyang R. Zhang:
Improved Regularization and Robustness for Fine-tuning in Neural Networks. 27249-27262 - Weizhe Yuan, Graham Neubig, Pengfei Liu:
BARTScore: Evaluating Generated Text as Text Generation. 27263-27277 - Ayoub Belhadji:
An analysis of Ermakov-Zolotukhin quadrature using kernels. 27278-27289 - Pan Zhou, Hanshu Yan, Xiaotong Yuan, Jiashi Feng, Shuicheng Yan:
Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond. 27290-27304 - Yuan Gao, Alex Peysakhovich, Christian Kroer:
Online Market Equilibrium with Application to Fair Division. 27305-27318 - Mingjian Zhu, Kai Han, Enhua Wu, Qiulin Zhang, Ying Nie, Zhenzhong Lan, Yunhe Wang:
Dynamic Resolution Network. 27319-27330 - Lingshen He, Yiming Dong, Yisen Wang, Dacheng Tao, Zhouchen Lin:
Gauge Equivariant Transformer. 27331-27343 - Antonia Creswell, Rishabh Kabra, Christopher P. Burgess, Murray Shanahan:
Unsupervised Object-Based Transition Models For 3D Partially Observable Environments. 27344-27355 - Songwei Ge, Shlok Mishra, Chun-Liang Li, Haohan Wang, David Jacobs:
Robust Contrastive Learning Using Negative Samples with Diminished Semantics. 27356-27368 - Haixiang Zhang, Yingjie Bi, Javad Lavaei:
General Low-rank Matrix Optimization: Geometric Analysis and Sharper Bounds. 27369-27380 - Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio:
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. 27381-27394 - Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai:
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning. 27395-27407 - Jungbeom Lee, Jooyoung Choi, Jisoo Mok, Sungroh Yoon:
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation. 27408-27421 - Ayush Sekhari, Karthik Sridharan, Satyen Kale:
SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs. 27422-27433 - R. David Evans, Tor M. Aamodt:
AC-GC: Lossy Activation Compression with Guaranteed Convergence. 27434-27448 - Alex Damian, Tengyu Ma, Jason D. Lee:
Label Noise SGD Provably Prefers Flat Global Minimizers. 27449-27461 - Sandesh Kamath, Amit Deshpande, Subrahmanyam Kambhampati Venkata, Vineeth N. Balasubramanian:
Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks. 27462-27474 - Yash Chandak, Scott Niekum, Bruno C. da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas:
Universal Off-Policy Evaluation. 27475-27490 - Yong Sheng Soh, Antonios Varvitsiotis:
A Non-commutative Extension of Lee-Seung's Algorithm for Positive Semidefinite Factorizations. 27491-27502 - Chris Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn:
Efficiently Identifying Task Groupings for Multi-Task Learning. 27503-27516 - Arantxa Casanova, Marlène Careil, Jakob Verbeek, Michal Drozdzal, Adriana Romero-Soriano:
Instance-Conditioned GAN. 27517-27529 - Brandon G. Jacques, Zoran Tiganj, Marc W. Howard, Per B. Sederberg:
DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales. 27530-27541 - Weishi Shi, Dayou Yu, Qi Yu
A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning. 27542-27554 - Cuong Tran, My H. Dinh, Ferdinando Fioretto:
Differentially Private Empirical Risk Minimization under the Fairness Lens. 27555-27565 - Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin:
A Unified View of cGANs with and without Classifiers. 27566-27579 - Julian Schrittwieser, Thomas Hubert, Amol Mandhane, Mohammadamin Barekatain, Ioannis Antonoglou, David Silver:
Online and Offline Reinforcement Learning by Planning with a Learned Model. 27580-27591 - Arun Verma, Manjesh Kumar Hanawal:
Stochastic Multi-Armed Bandits with Control Variates. 27592-27603 - Constantinos Daskalakis, Maxwell Fishelson, Noah Golowich:
Near-Optimal No-Regret Learning in General Games. 27604-27616 - Yu Wang, Jingyang Lin, Jingjing Zou, Yingwei Pan, Ting Yao, Tao Mei:
Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration. 27617-27630 - Michael L. Iuzzolino, Michael C. Mozer, Samy Bengio:
Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss. 27631-27644 - Chao Ma, Cheng Zhang:
Identifiable Generative models for Missing Not at Random Data Imputation. 27645-27658 - Benjamin Dupuis, Arthur Jacot:
DNN-based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel. 27659-27669 - Omar Khattab, Christopher Potts, Matei A. Zaharia:
Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval. 27670-27682 - Kimon Fountoulakis, Pan Li, Shenghao Yang:
Local Hyper-Flow Diffusion. 27683-27694 - Masahiro Nakano, Yasuhiro Fujiwara, Akisato Kimura, Takeshi Yamada, Naonori Ueda:
Permuton-induced Chinese Restaurant Process. 27695-27708 - Jonah Brown-Cohen:
Faster Algorithms and Constant Lower Bounds for the Worst-Case Expected Error. 27709-27719 - Trung Phung, Trung Le, Long Vuong, Toan Tran, Anh Tran, Hung Bui, Dinh Q. Phung:
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources. 27720-27733 - Yuming Shen, Ziyi Shen, Menghan Wang, Jie Qin, Philip H. S. Torr, Ling Shao:
You Never Cluster Alone. 27734-27746 - Yuan Chen, Wenbo Fei, Qinxia Wang, Donglin Zeng, Yuanjia Wang:
Dynamic COVID risk assessment accounting for community virus exposure from a spatial-temporal transmission model. 27747-27760 - Aadirupa Saha, Pierre Gaillard:
Dueling Bandits with Adversarial Sleeping. 27761-27771 - Alexander G. Reisach, Christof Seiler, Sebastian Weichwald:
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy to Game. 27772-27784 - Hanrui Zhang, Vincent Conitzer:
Automated Dynamic Mechanism Design. 27785-27797 - Alan Nawzad Amin, Eli N. Weinstein, Debora S. Marks:
A generative nonparametric Bayesian model for whole genomes. 27798-27812 - Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
Robust Predictable Control. 27813-27825 - Alexei Baevski, Wei-Ning Hsu, Alexis Conneau, Michael Auli:
Unsupervised Speech Recognition. 27826-27839 - Leslie Rice, Anna Bair, Huan Zhang, J. Zico Kolter:
Robustness between the worst and average case. 27840-27851 - Oumayma Bounou, Jean Ponce, Justin Carpentier:
Online Learning and Control of Complex Dynamical Systems from Sensory Input. 27852-27864 - Miltiadis Allamanis, Henry Jackson-Flux, Marc Brockschmidt:
Self-Supervised Bug Detection and Repair. 27865-27876 - Menachem Adelman, Kfir Y. Levy, Ido Hakimi, Mark Silberstein:
Faster Neural Network Training with Approximate Tensor Operations. 27877-27889 - Fan Yang, Kai He, Linxiao Yang, Hongxia Du, Jingbang Yang, Bo Yang, Liang Sun:
Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach. 27890-27902 - Yutong He, Dingjie Wang, Nicholas Lai, William Zhang, Chenlin Meng, Marshall Burke, David B. Lobell, Stefano Ermon:
Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis. 27903-27915 - Gerrit J. J. van den Burg, Christopher K. I. Williams:
On Memorization in Probabilistic Deep Generative Models. 27916-27928 - Weijie J. Su:
You Are the Best Reviewer of Your Own Papers: An Owner-Assisted Scoring Mechanism. 27929-27939 - Fangzhou Hong, Liang Pan, Zhongang Cai, Ziwei Liu:
Garment4D: Garment Reconstruction from Point Cloud Sequences. 27940-27951 - Shicong Cen, Yuting Wei, Yuejie Chi:
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization. 27952-27964 - Qi Zhu, Natalia Ponomareva, Jiawei Han, Bryan Perozzi:
Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data. 27965-27977 - Wentao Zhang, Yexin Wang, Zhenbang You, Meng Cao, Ping Huang, Jiulong Shan, Zhi Yang, Bin Cui:
RIM: Reliable Influence-based Active Learning on Graphs. 27978-27990 - Kevin C. Cheng, Shuchin Aeron, Michael C. Hughes, Eric L. Miller:
Dynamical Wasserstein Barycenters for Time-series Modeling. 27991-28003 - Thijs Vogels, Lie He, Anastasia Koloskova, Sai Praneeth Karimireddy, Tao Lin, Sebastian U. Stich, Martin Jaggi:
RelaySum for Decentralized Deep Learning on Heterogeneous Data. 28004-28015 - Jinwoo Kim, Saeyoon Oh, Seunghoon Hong:
Transformers Generalize DeepSets and Can be Extended to Graphs & Hypergraphs. 28016-28028 - Soumya Basu, Branislav Kveton, Manzil Zaheer, Csaba Szepesvári:
No Regrets for Learning the Prior in Bandits. 28029-28041 - Manli Shu, Zuxuan Wu, Micah Goldblum, Tom Goldstein:
Encoding Robustness to Image Style via Adversarial Feature Perturbations. 28042-28053 - Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Hadrien Hendrikx, Pierre Gaillard, Laurent Massoulié, Adrien B. Taylor:
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms. 28054-28066 - Ta-Chu Kao, Kristopher T. Jensen, Gido van de Ven, Alberto Bernacchia, Guillaume Hennequin:
Natural continual learning: success is a journey, not (just) a destination. 28067-28079 - Vitaly Feldman, Tijana Zrnic:
Individual Privacy Accounting via a Rényi Filter. 28080-28091 - Zhenhua Liu, Yunhe Wang, Kai Han, Wei Zhang, Siwei Ma, Wen Gao:
Post-Training Quantization for Vision Transformer. 28092-28103 - Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi:
Unsupervised Part Discovery from Contrastive Reconstruction. 28104-28118 - Guocheng Qian, Hasan Hammoud, Guohao Li, Ali K. Thabet, Bernard Ghanem:
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning. 28119-28130 - Ramakrishna Vedantam, David Lopez-Paz, David J. Schwab:
An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers. 28131-28143 - Mohammad Mahdi Khalili, Xueru Zhang, Mahed Abroshan:
Fair Sequential Selection Using Supervised Learning Models. 28144-28155 - Yue Sun, Adhyyan Narang, Halil Ibrahim Gulluk, Samet Oymak, Maryam Fazel:
Towards Sample-efficient Overparameterized Meta-learning. 28156-28168 - Husheng Han, Kaidi Xu, Xing Hu, Xiaobing Chen, Ling Liang, Zidong Du, Qi Guo, Yanzhi Wang, Yunji Chen:
ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers. 28169-28181 - Andrew K. Lampinen, Stephanie C. Y. Chan, Andrea Banino, Felix Hill:
Towards mental time travel: a hierarchical memory for reinforcement learning agents. 28182-28195 - Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization. 28196-28207 - Brendan O'Donoghue:
Variational Bayesian Reinforcement Learning with Regret Bounds. 28208-28221 - Aditya Bhaskara, Ashok Cutkosky
Logarithmic Regret from Sublinear Hints. 28222-28232 - Luigi Gresele, Julius von Kügelgen, Vincent Stimper, Bernhard Schölkopf, Michel Besserve:
Independent mechanism analysis, a new concept? 28233-28248 - Juntang Zhuang, Yifan Ding, Tommy Tang, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan:
Momentum Centering and Asynchronous Update for Adaptive Gradient Methods. 28249-28260 - Uddeshya Upadhyay, Yanbei Chen, Zeynep Akata:
Robustness via Uncertainty-aware Cycle Consistency. 28261-28273 - Guhyun Kim, Doo Seok Jeong:
CBP: backpropagation with constraint on weight precision using a pseudo-Lagrange multiplier method. 28274-28285 - Menachem Sadigurschi, Uri Stemmer:
On the Sample Complexity of Privately Learning Axis-Aligned Rectangles. 28286-28297 - Jiangyuan Li, Thanh Van Nguyen, Chinmay Hegde, Ka Wai Wong:
Implicit Sparse Regularization: The Impact of Depth and Early Stopping. 28298-28309 - Soumyadip Ghosh, Mark S. Squillante, Ebisa D. Wollega:
Efficient Generalization with Distributionally Robust Learning. 28310-28322 - Xi Wang, Zhipeng Tu, Yiguang Hong, Yingyi Wu, Guodong Shi:
No-regret Online Learning over Riemannian Manifolds. 28323-28335 - Junsu Kim, Younggyo Seo, Jinwoo Shin:
Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning. 28336-28349 - Alon Cohen, Yonathan Efroni, Yishay Mansour, Aviv Rosenberg:
Minimax Regret for Stochastic Shortest Path. 28350-28361 - Sofiène Jerbi, Casper Gyurik, Simon C. Marshall, Hans J. Briegel, Vedran Dunjko:
Parametrized Quantum Policies for Reinforcement Learning. 28362-28375 - Tim G. J. Rudner, Cong Lu, Michael A. Osborne, Yarin Gal, Yee Whye Teh:
On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations. 28376-28389 - Grigorios Chrysos, Markos Georgopoulos, Yannis Panagakis:
Conditional Generation Using Polynomial Expansions. 28390-28404 - Kwangjun Ahn, Sinho Chewi:
Efficient constrained sampling via the mirror-Langevin algorithm. 28405-28418 - Chenyang Wu, Guoyu Yang, Zongzhang Zhang, Yang Yu, Dong Li, Wulong Liu, Jianye Hao:
Adaptive Online Packing-guided Search for POMDPs. 28419-28430 - Stephen Chung, Hava T. Siegelmann:
Turing Completeness of Bounded-Precision Recurrent Neural Networks. 28431-28441 - Yi-Wen Chen, Yi-Hsuan Tsai, Ming-Hsuan Yang:
End-to-end Multi-modal Video Temporal Grounding. 28442-28453 - Colin White, Arber Zela, Robin Ru, Yang Liu, Frank Hutter:
How Powerful are Performance Predictors in Neural Architecture Search? 28454-28469 - Jinpeng Li, Yingce Xia, Rui Yan, Hongda Sun, Dongyan Zhao, Tie-Yan Liu:
Stylized Dialogue Generation with Multi-Pass Dual Learning. 28470-28481 - Marcel Hirt, Michalis K. Titsias, Petros Dellaportas:
Entropy-based adaptive Hamiltonian Monte Carlo. 28482-28495 - Maciej Wolczyk, Michal Zajac, Razvan Pascanu, Lukasz Kucinski, Piotr Milos:
Continual World: A Robotic Benchmark For Continual Reinforcement Learning. 28496-28510 - Liad Erez, Tomer Koren:
Towards Best-of-All-Worlds Online Learning with Feedback Graphs. 28511-28521 - Yufei Xu, Qiming Zhang, Jing Zhang, Dacheng Tao:
ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias. 28522-28535 - Wanyun Cui, Xingran Chen:
Open Rule Induction. 28536-28547 - Aurélien Bibaut, Maria Dimakopoulou, Nathan Kallus, Antoine Chambaz, Mark J. van der Laan:
Post-Contextual-Bandit Inference. 28548-28559 - Shaojie Li, Jie Wu, Xuefeng Xiao, Fei Chao, Xudong Mao, Rongrong Ji:
Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme. 28560-28572 - Kohei Miyaguchi:
Asymptotically Exact Error Characterization of Offline Policy Evaluation with Misspecified Linear Models. 28573-28584 - T. Anderson Keller, Max Welling:
Topographic VAEs learn Equivariant Capsules. 28585-28597 - Rahul Kidambi, Jonathan D. Chang, Wen Sun:
MobILE: Model-Based Imitation Learning From Observation Alone. 28598-28611 - Younghyun Park, Dong-Jun Han, Do-Yeon Kim, Jun Seo, Jaekyun Moon:
Few-Round Learning for Federated Learning. 28612-28622 - Ruiqi Gao, Jianwen Xie, Xue-Xin Wei, Song-Chun Zhu, Ying Nian Wu:
On Path Integration of Grid Cells: Group Representation and Isotropic Scaling. 28623-28635 - Guanghui Wang, Yuanyu Wan, Tianbao Yang, Lijun Zhang:
Online Convex Optimization with Continuous Switching Constraint. 28636-28647 - Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi:
Why Do Better Loss Functions Lead to Less Transferable Features? 28648-28662 - Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh:
Breaking the centralized barrier for cross-device federated learning. 28663-28676 - Priya L. Donti, Aayushya Agarwal, Neeraj Vijay Bedmutha, Larry T. Pileggi, J. Zico Kolter:
Adversarially robust learning for security-constrained optimal power flow. 28677-28689 - Gal Vardi, Gilad Yehudai, Ohad Shamir:
Learning a Single Neuron with Bias Using Gradient Descent. 28690-28700 - Mitchell Plyler, Michael Green, Min Chi:
Making a (Counterfactual) Difference One Rationale at a Time. 28701-28713 - Le Hui, Lingpeng Wang, Mingmei Cheng, Jin Xie, Jian Yang:
3D Siamese Voxel-to-BEV Tracker for Sparse Point Clouds. 28714-28727 - Keegan Harris, Hoda Heidari, Zhiwei Steven Wu:
Stateful Strategic Regression. 28728-28741 - Jannik Kossen, Neil Band, Clare Lyle, Aidan N. Gomez, Thomas Rainforth, Yarin Gal:
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning. 28742-28756 - Patrick J. Mineault, Shahab Bakhtiari, Blake A. Richards, Christopher C. Pack:
Your head is there to move you around: Goal-driven models of the primate dorsal pathway. 28757-28771 - Valentin Delchevalerie, Adrien Bibal, Benoît Frénay, Alexandre Mayer:
Achieving Rotational Invariance with Bessel-Convolutional Neural Networks. 28772-28783 - Jinxin Liu, Hao Shen, Donglin Wang, Yachen Kang, Qiangxing Tian:
Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning. 28784-28797 - Junhan Yang, Zheng Liu, Shitao Xiao, Chaozhuo Li, Defu Lian, Sanjay Agrawal, Amit Singh, Guangzhong Sun, Xing Xie:
GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graph. 28798-28810 - Sébastien Bubeck, Mark Sellke:
A Universal Law of Robustness via Isoperimetry. 28811-28822 - Emile Mathieu, Adam Foster, Yee Whye Teh:
On Contrastive Representations of Stochastic Processes. 28823-28835 - Sudeep Salgia, Sattar Vakili, Qing Zhao:
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance. 28836-28847 - Soledad Villar, David W. Hogg, Kate Storey-Fisher, Weichi Yao, Ben Blum-Smith:
Scalars are universal: Equivariant machine learning, structured like classical physics. 28848-28863 - Jiahao Xie, Xiaohang Zhan, Ziwei Liu, Yew Soon Ong, Chen Change Loy:
Unsupervised Object-Level Representation Learning from Scene Images. 28864-28876 - Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu:
Do Transformers Really Perform Badly for Graph Representation? 28877-28888 - Jonathan Schwarz, Siddhant M. Jayakumar, Razvan Pascanu, Peter E. Latham, Yee Whye Teh:
Powerpropagation: A sparsity inducing weight reparameterisation. 28889-28903 - Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang Wang, Zicheng Liu, Mei Chen, Lu Yuan:
Stronger NAS with Weaker Predictors. 28904-28918 - Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu:
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. 28919-28928 - Buddhima Gamlath, Xinrui Jia, Adam Polak, Ola Svensson:
Nearly-Tight and Oblivious Algorithms for Explainable Clustering. 28929-28939 - Tingran Wang, Sam Buchanan, Dar Gilboa, John Wright:
Deep Networks Provably Classify Data on Curves. 28940-28953 - Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn:
COMBO: Conservative Offline Model-Based Policy Optimization. 28954-28967 - Daniel Jarrett, Ioana Bica, Mihaela van der Schaar:
Time-series Generation by Contrastive Imitation. 28968-28982 - Sofya Raskhodnikova, Satchit Sivakumar, Adam D. Smith, Marika Swanberg:
Differentially Private Sampling from Distributions. 28983-28994 - Hanna Tseran, Guido Montúfar:
On the Expected Complexity of Maxout Networks. 28995-29008 - Hongji Yang, Xiufan Lu, Yingying Zhu:
Cross-view Geo-localization with Layer-to-Layer Transformer. 29009-29020 - Haonan Yu, Wei Xu, Haichao Zhang:
TAAC: Temporally Abstract Actor-Critic for Continuous Control. 29021-29033 - Dushyant Sahoo, Christos Davatzikos:
Learning Robust Hierarchical Patterns of Human Brain across Many fMRI Studies. 29034-29048 - Tanner Fiez, Lillian J. Ratliff, Eric Mazumdar, Evan Faulkner, Adhyyan Narang:
Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games. 29049-29063 - Aditya Gopalan, Braghadeesh Lakshminarayanan, Venkatesh Saligrama:
Bandit Quickest Changepoint Detection. 29064-29073 - Haoran Wang, Weitang Liu, Alex Bocchieri, Yixuan Li:
Can multi-label classification networks know what they don't know? 29074-29087 - Tong Wu, Liang Pan, Junzhe Zhang, Tai Wang, Ziwei Liu, Dahua Lin:
Balanced Chamfer Distance as a Comprehensive Metric for Point Cloud Completion. 29088-29100 - Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang:
Optimal Gradient-based Algorithms for Non-concave Bandit Optimization. 29101-29115 - Eduard Oravkin, Patrick Rebeschini:
On Optimal Interpolation in Linear Regression. 29116-29128 - Zihang Meng, Lopamudra Mukherjee, Yichao Wu, Vikas Singh, Sathya N. Ravi:
Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs. 29129-29141 - Jianhao Wang, Zhizhou Ren, Beining Han, Jianing Ye, Chongjie Zhang:
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization. 29142-29155 - Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang:
Margin-Independent Online Multiclass Learning via Convex Geometry. 29156-29167 - Zhi Zhou, Lan-Zhe Guo, Zhanzhan Cheng, Yufeng Li, Shiliang Pu:
STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data. 29168-29180 - Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi:
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning. 29181-29192 - Xisen Jin, Arka Sadhu, Junyi Du, Xiang Ren:
Gradient-based Editing of Memory Examples for Online Task-free Continual Learning. 29193-29205 - Ferran Alet, Maria Bauzá, Kenji Kawaguchi, Nurullah Giray Kuru, Tomás Lozano-Pérez, Leslie Pack Kaelbling:
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time. 29206-29217 - Scott Pesme, Loucas Pillaud-Vivien, Nicolas Flammarion:
Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity. 29218-29230 - Luyao Yuan, Dongruo Zhou, Junhong Shen, Jingdong Gao, Jeffrey L. Chen, Quanquan Gu, Ying Nian Wu, Song-Chun Zhu:
Iterative Teacher-Aware Learning. 29231-29245 - Vaibhav Saxena, Jimmy Ba, Danijar Hafner:
Clockwork Variational Autoencoders. 29246-29257 - Kun Su, Xiulong Liu, Eli Shlizerman:
How Does it Sound? 29258-29273 - Juan C. Perdomo, Jack Umenberger, Max Simchowitz:
Stabilizing Dynamical Systems via Policy Gradient Methods. 29274-29286 - Joshua Meier, Roshan Rao, Robert Verkuil, Jason Liu, Tom Sercu, Alexander Rives:
Language models enable zero-shot prediction of the effects of mutations on protein function. 29287-29303 - Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare:
Deep Reinforcement Learning at the Edge of the Statistical Precipice. 29304-29320 - Patrick H. Chen, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh:
DRONE: Data-aware Low-rank Compression for Large NLP Models. 29321-29334 - Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi:
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. 29335-29347 - Angeliki Lazaridou, Adhiguna Kuncoro, Elena Gribovskaya, Devang Agrawal, Adam Liska, Tayfun Terzi, Mai Gimenez, Cyprien de Masson d'Autume, Tomás Kociský, Sebastian Ruder, Dani Yogatama, Kris Cao, Susannah Young, Phil Blunsom:
Mind the Gap: Assessing Temporal Generalization in Neural Language Models. 29348-29363 - Melih Barsbey, Milad Sefidgaran, Murat A. Erdogdu, Gaël Richard, Umut Simsekli:
Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks. 29364-29378 - Cole L. Hurwitz, Akash Srivastava, Kai Xu, Justin Jude, Matthew G. Perich, Lee E. Miller, Matthias H. Hennig:
Targeted Neural Dynamical Modeling. 29379-29392 - Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui:
Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation. 29393-29405 - Zhenyu Huang, Guocheng Niu, Xiao Liu, Wenbiao Ding, Xinyan Xiao, Hua Wu, Xi Peng:
Learning with Noisy Correspondence for Cross-modal Matching. 29406-29419 - Jianhao Wang, Wenzhe Li, Haozhe Jiang, Guangxiang Zhu, Siyuan Li, Chongjie Zhang:
Offline Reinforcement Learning with Reverse Model-based Imagination. 29420-29432 - Boris Knyazev, Michal Drozdzal, Graham W. Taylor, Adriana Romero-Soriano:
Parameter Prediction for Unseen Deep Architectures. 29433-29448 - Tan M. Nguyen, Vai Suliafu, Stanley J. Osher, Long Chen, Bao Wang:
FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention. 29449-29463 - Junhui Zhang, Jingkai Yan, John Wright:
Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix Recovery. 29464-29475 - Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal A. C. Xhonneux, Jian Tang:
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction. 29476-29490 - Léo Lebrat, Rodrigo Santa Cruz, Frédéric de Gournay, Darren Fu, Pierrick Bourgeat, Jurgen Fripp, Clinton Fookes, Olivier Salvado:
CorticalFlow: A Diffeomorphic Mesh Transformer Network for Cortical Surface Reconstruction. 29491-29505 - Nan Ding, Xi Chen, Tomer Levinboim, Sebastian Goodman, Radu Soricut:
Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning. 29506-29516 - Steve Yadlowsky, Taedong Yun, Cory Y. McLean, Alexander D'Amour:
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. 29517-29528 - Suvir Mirchandani, Siddharth Karamcheti, Dorsa Sadigh:
ELLA: Exploration through Learned Language Abstraction. 29529-29540 - Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng, Wenjun Zhang:
Learning Distilled Collaboration Graph for Multi-Agent Perception. 29541-29552 - Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Geneviève Robin:
Federated-EM with heterogeneity mitigation and variance reduction. 29553-29566 - Ilja Kuzborskij, Csaba Szepesvári, Omar Rivasplata, Amal Rannen-Triki, Razvan Pascanu:
On the Role of Optimization in Double Descent: A Least Squares Study. 29567-29577 - Yanxi Li, Zhaohui Yang, Yunhe Wang, Chang Xu:
Neural Architecture Dilation for Adversarial Robustness. 29578-29589 - Yang Bai, Xin Yan, Yong Jiang, Shu-Tao Xia, Yisen Wang:
Clustering Effect of Adversarial Robust Models. 29590-29601 - Min Jae Song, Ilias Zadik, Joan Bruna:
On the Cryptographic Hardness of Learning Single Periodic Neurons. 29602-29615 - Marco Mondelli, Ramji Venkataramanan:
PCA Initialization for Approximate Message Passing in Rotationally Invariant Models. 29616-29629 - Chengyue Gong, Xingchao Liu, Qiang Liu:
Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach. 29630-29642 - Yifang Chen, Simon S. Du, Kevin G. Jamieson:
Corruption Robust Active Learning. 29643-29654 - Runzhe Wan, Lin Ge, Rui Song:
Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models. 29655-29668 - Yichen Yang, Jeevana Priya Inala, Osbert Bastani, Yewen Pu, Armando Solar-Lezama, Martin C. Rinard:
Program Synthesis Guided Reinforcement Learning for Partially Observed Environments. 29669-29683 - Zeyu Shen, Lodewijk Gelauff, Ashish Goel, Aleksandra Korolova, Kamesh Munagala
Robust Allocations with Diversity Constraints. 29684-29696 - Sunghyeon Woo, Jeongwoo Park, Jiwoo Hong, Dongsuk Jeon:
Activation Sharing with Asymmetric Paths Solves Weight Transport Problem without Bidirectional Connection. 29697-29709 - Mingcong Liu, Qiang Li, Zekui Qin, Guoxin Zhang, Pengfei Wan, Wen Zheng:
BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation. 29710-29722 - Prateek Jain, John Rush, Adam D. Smith, Shuang Song, Abhradeep Guha Thakurta:
Differentially Private Model Personalization. 29723-29735 - Nabarun Deb, Promit Ghosal, Bodhisattva Sen:
Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections. 29736-29753 - Tobias Sutter, Andreas Krause, Daniel Kuhn:
Robust Generalization despite Distribution Shift via Minimum Discriminating Information. 29754-29767 - Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael C. Mozer, Becca Roelofs:
Soft Calibration Objectives for Neural Networks. 29768-29779 - Lenart Treven, Philippe Wenk, Florian Dörfler, Andreas Krause:
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models. 29780-29793 - Tushar Nagarajan, Kristen Grauman:
Shaping embodied agent behavior with activity-context priors from egocentric video. 29794-29805 - Fan-Keng Sun, Christopher I. Lang, Duane S. Boning:
Adjusting for Autocorrelated Errors in Neural Networks for Time Series. 29806-29819 - Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu:
A Geometric Analysis of Neural Collapse with Unconstrained Features. 29820-29834 - Jason Y. Zhang, Gengshan Yang, Shubham Tulsiani, Deva Ramanan:
NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild. 29835-29847 - Yifan Zhang, Bryan Hooi, Dapeng Hu, Jian Liang, Jiashi Feng:
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning. 29848-29860 - Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh:
Discovery of Options via Meta-Learned Subgoals. 29861-29873 - Ankit Garg, Robin Kothari, Praneeth Netrapalli, Suhail Sherif:
Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness. 29874-29884 - Deli Chen, Yankai Lin, Guangxiang Zhao, Xuancheng Ren, Peng Li, Jie Zhou, Xu Sun:
Topology-Imbalance Learning for Semi-Supervised Node Classification. 29885-29897 - Jinwoo Jeon, Jaechang Kim
Gradient Inversion with Generative Image Prior. 29898-29908 - Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter:
Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification. 29909-29921 - Erik H. Thiede, Wenda Zhou, Risi Kondor:
Autobahn: Automorphism-based Graph Neural Nets. 29922-29934 - Sylvestre-Alvise Rebuffi, Sven Gowal, Dan Andrei Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann:
Data Augmentation Can Improve Robustness. 29935-29948 - Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Bernie Wang, Tim Januschowski:
Deep Explicit Duration Switching Models for Time Series. 29949-29961 - Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvärinen:
Shared Independent Component Analysis for Multi-Subject Neuroimaging. 29962-29971 - Denys Rozumnyi, Martin R. Oswald, Vittorio Ferrari, Marc Pollefeys:
Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects. 29972-29983 - Cem Kalkanli, Ayfer Özgür:
Batched Thompson Sampling. 29984-29994 - Ligeng Zhu, Hongzhou Lin, Yao Lu, Yujun Lin, Song Han:
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning. 29995-30007 - Jianwei Yang, Chunyuan Li, Pengchuan Zhang, Xiyang Dai, Bin Xiao, Lu Yuan, Jianfeng Gao:
Focal Attention for Long-Range Interactions in Vision Transformers. 30008-30022 - Harry Bendekgey, Erik B. Sudderth:
Scalable and Stable Surrogates for Flexible Classifiers with Fairness Constraints. 30023-30036 - Marc Finzi, Greg Benton, Andrew Gordon Wilson:
Residual Pathway Priors for Soft Equivariance Constraints. 30037-30049 - Aadirupa Saha:
Optimal Algorithms for Stochastic Contextual Preference Bandits. 30050-30062 - Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai:
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize. 30063-30074 - Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang:
Learning Large Neighborhood Search Policy for Integer Programming. 30075-30087 - Prathamesh Dharangutte, Christopher Musco:
Dynamic Trace Estimation. 30088-30099 - Ofir Nachum, Mengjiao Yang:
Provable Representation Learning for Imitation with Contrastive Fourier Features. 30100-30112 - Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden, Mark Rowland:
MICo: Improved representations via sampling-based state similarity for Markov decision processes. 30113-30126 - Stratis Tsirtsis, Abir De, Manuel Rodriguez:
Counterfactual Explanations in Sequential Decision Making Under Uncertainty. 30127-30139 - Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli:
Streaming Linear System Identification with Reverse Experience Replay. 30140-30152 - Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, Do-Guk Kim, Jinwoo Shin:
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness. 30153-30168 - Jiangxin Sun, Zihang Lin, Xintong Han, Jian-Fang Hu, Jia Xu, Wei-Shi Zheng:
Action-guided 3D Human Motion Prediction. 30169-30180 - Maksym Yatsura, Jan Hendrik Metzen, Matthias Hein:
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks. 30181-30195 - Zeru Zhang, Jiayin Jin, Zijie Zhang, Yang Zhou, Xin Zhao, Jiaxiang Ren, Ji Liu, Lingfei Wu, Ruoming Jin, Dejing Dou:
Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory. 30196-30210 - Shangshu Qian, Hung Viet Pham, Thibaud Lutellier, Zeou Hu, Jungwon Kim, Lin Tan, Yaoliang Yu, Jiahao Chen, Sameena Shah:
Are My Deep Learning Systems Fair? An Empirical Study of Fixed-Seed Training. 30211-30227 - Anthony L. Caterini, Gabriel Loaiza-Ganem, Geoff Pleiss, John P. Cunningham:
Rectangular Flows for Manifold Learning. 30228-30241 - Chang Liu, Haoyue Tang, Tao Qin, Jintao Wang, Tie-Yan Liu:
On the Generative Utility of Cyclic Conditionals. 30242-30256 - Dhawal Gupta, Gabor Mihucz, Matthew Schlegel, James E. Kostas, Philip S. Thomas, Martha White:
Structural Credit Assignment in Neural Networks using Reinforcement Learning. 30257-30270 - Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang:
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum. 30271-30283 - Erik Englesson, Hossein Azizpour:
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels. 30284-30297 - Oleksiy Ostapenko, Pau Rodríguez, Massimo Caccia, Laurent Charlin:
Continual Learning via Local Module Composition. 30298-30312 - Hung Le, Thommen George Karimpanal, Majid Abdolshah, Truyen Tran, Svetha Venkatesh:
Model-Based Episodic Memory Induces Dynamic Hybrid Controls. 30313-30325 - Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen:
FedDR - Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization. 30326-30338 - Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojciech Czaja, Tom Goldstein:
Adversarial Examples Make Strong Poisons. 30339-30351 - Ibrahim Jubran, Ernesto Evgeniy Sanches Shayda, Ilan Newman, Dan Feldman:
Coresets for Decision Trees of Signals. 30352-30364 - Bernd Illing, Jean Ventura, Guillaume Bellec, Wulfram Gerstner:
Local plasticity rules can learn deep representations using self-supervised contrastive predictions. 30365-30379 - Hao Xue, Flora D. Salim, Yongli Ren, Nuria Oliver:
MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction. 30380-30391 - Tete Xiao, Mannat Singh, Eric Mintun, Trevor Darrell, Piotr Dollár, Ross B. Girshick:
Early Convolutions Help Transformers See Better. 30392-30400 - Xun Qian, Peter Richtárik, Tong Zhang:
Error Compensated Distributed SGD Can Be Accelerated. 30401-30413 - Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, Xiang Zhang:
InfoGCL: Information-Aware Graph Contrastive Learning. 30414-30425 - Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara:
Meta-Learning for Relative Density-Ratio Estimation. 30426-30438 - Vivien Cabannes, Loucas Pillaud-Vivien, Francis R. Bach, Alessandro Rudi:
Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning. 30439-30451 - Yunzhen Yao, Liangzu Peng, Manolis C. Tsakiris:
Unlabeled Principal Component Analysis. 30452-30464 - Andrew Jesson, Panagiotis Tigas, Joost van Amersfoort, Andreas Kirsch, Uri Shalit, Yarin Gal:
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data. 30465-30478 - Zhuo Wang, Wei Zhang, Ning Liu, Jianyong Wang:
Scalable Rule-Based Representation Learning for Interpretable Classification. 30479-30491 - Na Dong, Yongqiang Zhang, Mingli Ding, Gim Hee Lee:
Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection. 30492-30503 - Keerti Anand, Rong Ge, Amit Kumar, Debmalya Panigrahi:
A Regression Approach to Learning-Augmented Online Algorithms. 30504-30517
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