• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 2,335 matches

• 2021
• 
  Ahmed Abbas, Paul Swoboda:
  Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach. NeurIPS 2021: 15635-15649
• 
  Emmanuel Abbe, Enric Boix-Adserà, Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj:
  The staircase property: How hierarchical structure can guide deep learning. NeurIPS 2021: 26989-27002
• 
  Emmanuel Abbe, Pritish Kamath, Eran Malach, Colin Sandon, Nathan Srebro:
  On the Power of Differentiable Learning versus PAC and SQ Learning. NeurIPS 2021: 24340-24351
• 
  Milad Abdollahzadeh, Touba Malekzadeh, Ngai-Man Cheung:
  Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning. NeurIPS 2021: 14632-14644
• 
  David Abel, Will Dabney, Anna Harutyunyan, Mark K. Ho, Michael L. Littman, Doina Precup, Satinder Singh:
  On the Expressivity of Markov Reward. NeurIPS 2021: 7799-7812
• 
  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. NeurIPS 2021: 11883-11895
• 
  Mikkel Abrahamsen, Linda Kleist, Tillmann Miltzow:
  Training Neural Networks is ER-complete. NeurIPS 2021: 18293-18306
• 
  Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan:
  Implicit SVD for Graph Representation Learning. NeurIPS 2021: 8419-8431
• 
  Jayadev Acharya, Clément L. Canonne, Yuhan Liu, Ziteng Sun, Himanshu Tyagi:
  Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition. NeurIPS 2021: 18920-18931
• 
  Jayadev Acharya, Clément L. Canonne, Prathamesh Mayekar, Himanshu Tyagi:
  Information-constrained optimization: can adaptive processing of gradients help? NeurIPS 2021: 7126-7138
• 
  Jayadev Acharya, Clément L. Canonne, Aditya Vikram Singh, Himanshu Tyagi:
  Optimal Rates for Nonparametric Density Estimation under Communication Constraints. NeurIPS 2021: 26754-26766
• 
  Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya:
  Personalized Federated Learning With Gaussian Processes. NeurIPS 2021: 8392-8406
• 
  David Acuna, Jonah Philion, Sanja Fidler:
  Towards Optimal Strategies for Training Self-Driving Perception Models in Simulation. NeurIPS 2021: 1686-1699
• 
  Vincent Adam, Paul E. Chang, Mohammad Emtiyaz Khan, Arno Solin:
  Dual Parameterization of Sparse Variational Gaussian Processes. NeurIPS 2021: 11474-11486
• 
  Jeffrey Adams, Niels Hansen, Kun Zhang:
  Identification of Partially Observed Linear Causal Models: Graphical Conditions for the Non-Gaussian and Heterogeneous Cases. NeurIPS 2021: 22822-22833
• 
  Raghavendra Addanki, Shiva Prasad Kasiviswanathan:
  Collaborative Causal Discovery with Atomic Interventions. NeurIPS 2021: 12761-12773
• 
  Menachem Adelman, Kfir Y. Levy, Ido Hakimi, Mark Silberstein:
  Faster Neural Network Training with Approximate Tensor Operations. NeurIPS 2021: 27877-27889
• 
  Ishaq Aden-Ali, Hassan Ashtiani, Christopher Liaw:
  Privately Learning Mixtures of Axis-Aligned Gaussians. NeurIPS 2021: 3925-3938
• 
  Deeksha Adil, Brian Bullins, Sushant Sachdeva:
  Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization. NeurIPS 2021: 19122-19133
• 
  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. NeurIPS 2021: 18564-18576
• 
  Naman Agarwal, Peter Kairouz, Ziyu Liu:
  The Skellam Mechanism for Differentially Private Federated Learning. NeurIPS 2021: 5052-5064
• 
  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. NeurIPS 2021: 4699-4711
• 
  Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare:
  Deep Reinforcement Learning at the Edge of the Statistical Precipice. NeurIPS 2021: 29304-29320
• 
  Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun:
  On sensitivity of meta-learning to support data. NeurIPS 2021: 20447-20460
• 
  Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas:
  Dynamic Causal Bayesian Optimization. NeurIPS 2021: 10549-10560
• 
  Abhinav Agrawal, Justin Domke:
  Amortized Variational Inference for Simple Hierarchical Models. NeurIPS 2021: 21388-21399
• 
  Shubhada Agrawal, Wouter M. Koolen, Sandeep Juneja:
  Optimal Best-Arm Identification Methods for Tail-Risk Measures. NeurIPS 2021: 25578-25590
• 
  Kwangjun Ahn, Sinho Chewi:
  Efficient constrained sampling via the mirror-Langevin algorithm. NeurIPS 2021: 28405-28418
• 
  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. NeurIPS 2021: 3438-3450
• 
  Qingzhong Ai, Lirong He, Shiyu Liu, Zenglin Xu:
  ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE. NeurIPS 2021: 5910-5920

skipping 2,305 more matches