khoatranrb / icml2020-paper

ICML2020 Paper

This repo contains ICML2020 papers. It is cloned from this source.

Title	Aut	Paper	Sup
Selective Dyna-Style Planning Under Limited Model Capacity	Zaheer Abbas, Samuel Sokota, Erin Talvitie, Martha White	Link	Link
A distributional view on multi-objective policy optimization	Abbas Abdolmaleki, Sandy Huang, Leonard Hasenclever, Michael Neunert, Francis Song, Martina Zambelli, Murilo Martins, Nicolas Heess, Raia Hadsell, Martin Riedmiller	Link	Link
Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation	Marc Abeille, Alessandro Lazaric	Link	Link
Super-efficiency of automatic differentiation for functions defined as a minimum	Pierre Ablin, Gabriel Peyré, Thomas Moreau	Link	Link
A Geometric Approach to Archetypal Analysis via Sparse Projections	Vinayak Abrol, Pulkit Sharma	Link	Link
Context Aware Local Differential Privacy	Jayadev Acharya, Kallista Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun	Link	Link
Efficient Intervention Design for Causal Discovery with Latents	Raghavendra Addanki, Shiva Kasiviswanathan, Andrew Mcgregor, Cameron Musco	Link	Link
The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of Generalization	Ben Adlam, Jeffrey Pennington	Link	Link
Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial Corruptions	Arpit Agarwal, Shivani Agarwal, Sanjeev Khanna, Prathamesh Patil	Link	Link
Boosting for Control of Dynamical Systems	Naman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu	Link	Link
An Optimistic Perspective on Offline Reinforcement Learning	Rishabh Agarwal, Dale Schuurmans, Mohammad Norouzi	Link	Link
Optimal Bounds between f-Divergences and Integral Probability Metrics	Rohit Agrawal, Thibaut Horel	Link	None
LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments	Ali Ahmaditeshnizi, Saber Salehkaleybar, Negar Kiyavash	Link	Link
Learning What to Defer for Maximum Independent Sets	Sungsoo Ahn, Younggyo Seo, Jinwoo Shin	Link	Link
Invariant Risk Minimization Games	Kartik Ahuja, Karthikeyan Shanmugam, Kush Varshney, Amit Dhurandhar	Link	Link
Why bigger is not always better: on finite and infinite neural networks	Laurence Aitchison	Link	None
Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions	Ahmed Alaa, Mihaela Van Der Schaar	Link	Link
Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions	Ahmed Alaa, Mihaela Van Der Schaar	Link	Link
Random extrapolation for primal-dual coordinate descent	Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher	Link	Link
A new regret analysis for Adam-type algorithms	Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher	Link	Link
Restarted Bayesian Online Change-point Detector achieves Optimal Detection Delay	Reda Alami, Odalric Maillard, Raphael Feraud	Link	Link
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation	Amr Alexandari, Anshul Kundaje, Avanti Shrikumar	Link	Link
The Implicit Regularization of Stochastic Gradient Flow for Least Squares	Alnur Ali, Edgar Dobriban, Ryan Tibshirani	Link	Link
Structural Language Models of Code	Uri Alon, Roy Sadaka, Omer Levy, Eran Yahav	Link	Link
LowFER: Low-rank Bilinear Pooling for Link Prediction	Saadullah Amin, Stalin Varanasi, Katherine Ann Dunfield, Günter Neumann	Link	Link
Discount Factor as a Regularizer in Reinforcement Learning	Ron Amit, Ron Meir, Kamil Ciosek	Link	Link
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"	Saeed Amizadeh, Hamid Palangi, Alex Polozov, Yichen Huang, Kazuhito Koishida	Link	Link
The Differentiable Cross-Entropy Method	Brandon Amos, Denis Yarats	Link	Link
Customizing ML Predictions for Online Algorithms	Keerti Anand, Rong Ge, Debmalya Panigrahi	Link	Link
Fairwashing explanations with off-manifold detergent	Christopher Anders, Plamen Pasliev, Ann-Kathrin Dombrowski, Klaus-Robert Müller, Pan Kessel	Link	Link
Population-Based Black-Box Optimization for Biological Sequence Design	Christof Angermueller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy Colwell, D Sculley	Link	Link
Low-loss connection of weight vectors: distribution-based approaches	Ivan Anokhin, Dmitry Yarotsky	Link	Link
Online metric algorithms with untrusted predictions	Antonios Antoniadis, Christian Coester, Marek Elias, Adam Polak, Bertrand Simon	Link	Link
NADS: Neural Architecture Distribution Search for Uncertainty Awareness	Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian	Link	Link
Provable Representation Learning for Imitation Learning via Bi-level Optimization	Sanjeev Arora, Simon Du, Sham Kakade, Yuping Luo, Nikunj Saunshi	Link	Link
Quantum Boosting	Srinivasan Arunachalam, Reevu Maity	Link	Link
Black-box Certification and Learning under Adversarial Perturbations	Hassan Ashtiani, Vinayak Pathak, Ruth Urner	Link	Link
Invertible generative models for inverse problems: mitigating representation error and dataset bias	Muhammad Asim, Max Daniels, Oscar Leong, Ali Ahmed, Paul Hand	Link	Link
On the Convergence of Nesterov’s Accelerated Gradient Method in Stochastic Settings	Mahmoud Assran, Mike Rabbat	Link	Link
Safe screening rules for L0-regression from Perspective Relaxations	Alper Atamturk, Andres Gomez	Link	Link
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks	Pranjal Awasthi, Natalie Frank, Mehryar Mohri	Link	Link
Sample Amplification: Increasing Dataset Size even when Learning is Impossible	Brian Axelrod, Shivam Garg, Vatsal Sharan, Gregory Valiant	Link	Link
Sparse Convex Optimization via Adaptively Regularized Hard Thresholding	Kyriakos Axiotis, Maxim Sviridenko	Link	Link
Model-Based Reinforcement Learning with Value-Targeted Regression	Alex Ayoub, Zeyu Jia, Csaba Szepesvari, Mengdi Wang, Lin Yang	Link	Link
Forecasting Sequential Data Using Consistent Koopman Autoencoders	Omri Azencot, N. Benjamin Erichson, Vanessa Lin, Michael Mahoney	Link	Link
Constant Curvature Graph Convolutional Networks	Gregor Bachmann, Gary Becigneul, Octavian Ganea	Link	Link
Scalable Nearest Neighbor Search for Optimal Transport	Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner	Link	Link
Agent57: Outperforming the Atari Human Benchmark	Adrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Charles Blundell	Link	Link
Fiduciary Bandits	Gal Bahar, Omer Ben-Porat, Kevin Leyton-Brown, Moshe Tennenholtz	Link	Link
Learning De-biased Representations with Biased Representations	Hyojin Bahng, Sanghyuk Chun, Sangdoo Yun, Jaegul Choo, Seong Joon Oh	Link	Link
Deep k-NN for Noisy Labels	Dara Bahri, Heinrich Jiang, Maya Gupta	Link	Link
Provable Self-Play Algorithms for Competitive Reinforcement Learning	Yu Bai, Chi Jin	Link	Link
Sparse Subspace Clustering with Entropy-Norm	Liang Bai, Jiye Liang	Link	None
Coresets for Clustering in Graphs of Bounded Treewidth	Daniel Baker, Vladimir Braverman, Lingxiao Huang, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu	Link	Link
Refined bounds for algorithm configuration: The knife-edge of dual class approximability	Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik	Link	Link
Ready Policy One: World Building Through Active Learning	Philip Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts	Link	Link
Stochastic Optimization for Regularized Wasserstein Estimators	Marin Ballu, Quentin Berthet, Francis Bach	Link	Link
Dual Mirror Descent for Online Allocation Problems	Santiago Balseiro, Haihao Lu, Vahab Mirrokni	Link	Link
Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters	Subho Banerjee, Saurabh Jha, Zbigniew Kalbarczyk, Ravishankar Iyer	Link	Link
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training	Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, Hsiao-Wuen Hon	Link	Link
Fast OSCAR and OWL Regression via Safe Screening Rules	Runxue Bao, Bin Gu, Heng Huang	Link	None
Option Discovery in the Absence of Rewards with Manifold Analysis	Amitay Bar, Ronen Talmon, Ron Meir	Link	Link
Learning the piece-wise constant graph structure of a varying Ising model	Batiste Le Bars, Pierre Humbert, Argyris Kalogeratos, Nicolas Vayatis	Link	Link
Frequency Bias in Neural Networks for Input of Non-Uniform Density	Ronen Basri, Meirav Galun, Amnon Geifman, David Jacobs, Yoni Kasten, Shira Kritchman	Link	Link
Private Query Release Assisted by Public Data	Raef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan Ullman, Steven Wu	Link	None
ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications	Kinjal Basu, Amol Ghoting, Rahul Mazumder, Yao Pan	Link	Link
On Second-Order Group Influence Functions for Black-Box Predictions	Samyadeep Basu, Xuchen You, Soheil Feizi	Link	Link
Kernel interpolation with continuous volume sampling	Ayoub Belhadji, Rémi Bardenet, Pierre Chainais	Link	Link
Decoupled Greedy Learning of CNNs	Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon	Link	Link
The Cost-free Nature of Optimally Tuning Tikhonov Regularizers and Other Ordered Smoothers	Pierre Bellec, Dana Yang	Link	Link
Defense Through Diverse Directions	Christopher Bender, Yang Li, Yifeng Shi, Michael K. Reiter, Junier Oliva	Link	Link
Interference and Generalization in Temporal Difference Learning	Emmanuel Bengio, Joelle Pineau, Doina Precup	Link	Link
Preselection Bandits	Viktor Bengs, Eyke Hüllermeier	Link	Link
Efficient Policy Learning from Surrogate-Loss Classification Reductions	Andrew Bennett, Nathan Kallus	Link	Link
Training Neural Networks for and by Interpolation	Leonard Berrada, Andrew Zisserman, M. Pawan Kumar	Link	Link
Implicit differentiation of Lasso-type models for hyperparameter optimization	Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon	Link	Link
Online Learning with Imperfect Hints	Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit	Link	Link
When are Non-Parametric Methods Robust?	Robi Bhattacharjee, Kamalika Chaudhuri	Link	Link
Learning and Sampling of Atomic Interventions from Observations	Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, Vinodchandran N. Variyam	Link	Link
Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures	Chiranjib Bhattacharyya, Ravindran Kannan	Link	Link
Low-Rank Bottleneck in Multi-head Attention Models	Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank Reddi, Sanjiv Kumar	Link	Link
Spectral Clustering with Graph Neural Networks for Graph Pooling	Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi	Link	Link
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders	Ioana Bica, Ahmed Alaa, Mihaela Van Der Schaar	Link	Link
Adversarial Robustness for Code	Pavol Bielik, Martin Vechev	Link	Link
The Boomerang Sampler	Joris Bierkens, Sebastiano Grazzi, Kengo Kamatani, Gareth Roberts	Link	Link
Tight Bounds on Minimax Regret under Logarithmic Loss via Self-Concordance	Blair Bilodeau, Dylan Foster, Daniel Roy	Link	Link
My Fair Bandit: Distributed Learning of Max-Min Fairness with Multi-player Bandits	Ilai Bistritz, Tavor Baharav, Amir Leshem, Nicholas Bambos	Link	None
Provable guarantees for decision tree induction: the agnostic setting	Guy Blanc, Jane Lange, Li-Yang Tan	Link	Link
Fast Differentiable Sorting and Ranking	Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga	Link	Link
Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization?	Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry	Link	Link
Modulating Surrogates for Bayesian Optimization	Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill Campbell, Carl Henrik Ek	Link	Link
Deep Coordination Graphs	Wendelin Boehmer, Vitaly Kurin, Shimon Whiteson	Link	Link
Lorentz Group Equivariant Neural Network for Particle Physics	Alexander Bogatskiy, Brandon Anderson, Jan Offermann, Marwah Roussi, David Miller, Risi Kondor	Link	[Link](https://github.com/ fizisist/LorentzGroupNetwork)
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More	Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann	Link	Link
Proper Network Interpretability Helps Adversarial Robustness in Classification	Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel	Link	Link
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks	Blake Bordelon, Abdulkadir Canatar, Cengiz Pehlevan	Link	Link
Small Data, Big Decisions: Model Selection in the Small-Data Regime	Jorg Bornschein, Francesco Visin, Simon Osindero	Link	Link
Latent Variable Modelling with Hyperbolic Normalizing Flows	Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, Will Hamilton	Link	Link
Tightening Exploration in Upper Confidence Reinforcement Learning	Hippolyte Bourel, Odalric Maillard, Mohammad Sadegh Talebi	Link	Link
Preference Modeling with Context-Dependent Salient Features	Amanda Bower, Laura Balzano	Link	Link
Adversarial Filters of Dataset Biases	Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew Peters, Ashish Sabharwal, Yejin Choi	Link	Link
Calibration, Entropy Rates, and Memory in Language Models	Mark Braverman, Xinyi Chen, Sham Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang	Link	Link
Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension	Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan, Roi Sinoff	Link	Link
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference	Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan	Link	Link
Estimating the Number and Effect Sizes of Non-null Hypotheses	Jennifer Brennan, Ramya Korlakai Vinayak, Kevin Jamieson	Link	Link
The FAST Algorithm for Submodular Maximization	Adam Breuer, Eric Balkanski, Yaron Singer	Link	Link
GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation	Marc Brockschmidt	Link	Link
TaskNorm: Rethinking Batch Normalization for Meta-Learning	John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard Turner	Link	Link
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences	Daniel Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum	Link	Link
A Pairwise Fair and Community-preserving Approach to k-Center Clustering	Brian Brubach, Darshan Chakrabarti, John Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas	Link	Link
Scalable Exact Inference in Multi-Output Gaussian Processes	Wessel Bruinsma, Eric Perim, William Tebbutt, Scott Hosking, Arno Solin, Richard Turner	Link	Link
Online Pricing with Offline Data: Phase Transition and Inverse Square Law	Jinzhi Bu, David Simchi-Levi, Yunzong Xu	Link	None
Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models	Rares-Darius Buhai, Yoni Halpern, Yoon Kim, Andrej Risteski, David Sontag	Link	Link
DeBayes: a Bayesian Method for Debiasing Network Embeddings	Maarten Buyl, Tijl De Bie	Link	Link
Structured Prediction with Partial Labelling through the Infimum Loss	Vivien Cabannnes, Alessandro Rudi, Francis Bach	Link	Link
Online Learned Continual Compression with Adaptive Quantization Modules	Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau	Link	Link
Boosted Histogram Transform for Regression	Yuchao Cai, Hanyuan Hang, Hanfang Yang, Zhouchen Lin	Link	Link
On Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies	Hengrui Cai, Wenbin Lu, Rui Song	Link	Link
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality	Changxiao Cai, H. Vincent Poor, Yuxin Chen	Link	None
Provably Efficient Exploration in Policy Optimization	Qi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang	Link	Link
Near-linear time Gaussian process optimization with adaptive batching and resparsification	Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco	Link	Link
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates	Jeff Calder, Brendan Cook, Matthew Thorpe, Dejan Slepcev	Link	Link
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills	Victor Campos, Alexander Trott, Caiming Xiong, Richard Socher, Xavier Giro-I-Nieto, Jordi Torres	Link	Link
Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently	Asaf Cassel, Alon Cohen, Tomer Koren	Link	Link
Fully Parallel Hyperparameter Search: Reshaped Space-Filling	Marie-Liesse Cauwet, Camille Couprie, Julien Dehos, Pauline Luc, Jeremy Rapin, Morgane Riviere, Fabien Teytaud, Olivier Teytaud, Nicolas Usunier	Link	Link
Data preprocessing to mitigate bias: A maximum entropy based approach	L. Elisa Celis, Vijay Keswani, Nisheeth Vishnoi	Link	Link
Meta-learning with Stochastic Linear Bandits	Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil	Link	Link
Description Based Text Classification with Reinforcement Learning	Duo Chai, Wei Wu, Qinghong Han, Fei Wu, Jiwei Li	Link	Link
Concise Explanations of Neural Networks using Adversarial Training	Prasad Chalasani, Jiefeng Chen, Amrita Roy Chowdhury, Xi Wu, Somesh Jha	Link	Link
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift	Alex Chan, Ahmed Alaa, Zhaozhi Qian, Mihaela Van Der Schaar	Link	Link
Imputer: Sequence Modelling via Imputation and Dynamic Programming	William Chan, Chitwan Saharia, Geoffrey Hinton, Mohammad Norouzi, Navdeep Jaitly	Link	None
Optimizing for the Future in Non-Stationary MDPs	Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip Thomas	Link	Link
Learning to Simulate and Design for Structural Engineering	Kai-Hung Chang, Chin-Yi Cheng	Link	Link
Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions	Michael Chang, Sid Kaushik, S. Matthew Weinberg, Tom Griffiths, Sergey Levine	Link	Link
Invariant Rationalization	Shiyu Chang, Yang Zhang, Mo Yu, Tommi Jaakkola	Link	Link
Circuit-Based Intrinsic Methods to Detect Overfitting	Satrajit Chatterjee, Alan Mishchenko	Link	None
Better depth-width trade-offs for neural networks through the lens of dynamical systems	Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas	Link	Link
Explainable and Discourse Topic-aware Neural Language Understanding	Yatin Chaudhary, Hinrich Schuetze, Pankaj Gupta	Link	Link
Uncertainty-Aware Lookahead Factor Models for Quantitative Investing	Lakshay Chauhan, John Alberg, Zachary Lipton	Link	Link
Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning	Di Chen, Yiwei Bai, Wenting Zhao, Sebastian Ament, John Gregoire, Carla Gomes	Link	None
Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training	Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gong, Kewei Chen, Zhangyang Wang	Link	Link
Learning To Stop While Learning To Predict	Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song	Link	Link
Combinatorial Pure Exploration for Dueling Bandit	Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao	Link	Link
Graph Optimal Transport for Cross-Domain Alignment	Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin, Jingjing Liu	Link	Link
Stabilizing Differentiable Architecture Search via Perturbation-based Regularization	Xiangning Chen, Cho-Jui Hsieh	Link	Link
Mapping natural-language problems to formal-language solutions using structured neural representations	Kezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Ken Forbus, Jianfeng Gao	Link	Link
Convolutional Kernel Networks for Graph-Structured Data	Dexiong Chen, Laurent Jacob, Julien Mairal	Link	Link
Learning Flat Latent Manifolds with VAEs	Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick Van Der Smagt	Link	Link
A Simple Framework for Contrastive Learning of Visual Representations	Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey Hinton	Link	Link
Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search	Binghong Chen, Chengtao Li, Hanjun Dai, Le Song	Link	Link
Differentiable Product Quantization for End-to-End Embedding Compression	Ting Chen, Lala Li, Yizhou Sun	Link	Link
On Efficient Constructions of Checkpoints	Yu Chen, Zhenming Liu, Bin Ren, Xin Jin	Link	None
Angular Visual Hardness	Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Animashree Anandkumar	Link	Link
Estimating the Error of Randomized Newton Methods: A Bootstrap Approach	Jessie X.T. Chen, Miles Lopes	Link	None
VFlow: More Expressive Generative Flows with Variational Data Augmentation	Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian	Link	Link
More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models	Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi	Link	Link
An Accelerated DFO Algorithm for Finite-sum Convex Functions	Yuwen Chen, Antonio Orvieto, Aurelien Lucchi	Link	Link
Generative Pretraining From Pixels	Mark Chen, Alec Radford, Rewon Child, Jeffrey Wu, Heewoo Jun, David Luan, Ilya Sutskever	Link	Link
Negative Sampling in Semi-Supervised learning	John Chen, Vatsal Shah, Anastasios Kyrillidis	Link	Link
Optimization from Structured Samples for Coverage Functions	Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang	Link	None
Simple and Deep Graph Convolutional Networks	Ming Chen, Zhewei Wei, Zengfeng Huang, Bolin Ding, Yaliang Li	Link	Link
On Breaking Deep Generative Model-based Defenses and Beyond	Yanzhi Chen, Renjie Xie, Zhanxing Zhu	Link	Link
Automated Synthetic-to-Real Generalization	Wuyang Chen, Zhiding Yu, Zhangyang Wang, Animashree Anandkumar	Link	Link
(Locally) Differentially Private Combinatorial Semi-Bandits	Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang	Link	Link
High-dimensional Robust Mean Estimation via Gradient Descent	Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi	Link	Link
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information	Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, Lawrence Carin	Link	Link
Learning with Bounded Instance and Label-dependent Label Noise	Jiacheng Cheng, Tongliang Liu, Kotagiri Ramamohanarao, Dacheng Tao	Link	Link
Mutual Transfer Learning for Massive Data	Ching-Wei Cheng, Xingye Qiao, Guang Cheng	Link	Link
Stochastic Gradient and Langevin Processes	Xiang Cheng, Dong Yin, Peter Bartlett, Michael Jordan	Link	Link
Representation Learning via Adversarially-Contrastive Optimal Transport	Anoop Cherian, Shuchin Aeron	Link	Link
Convergence Rates of Variational Inference in Sparse Deep Learning	Badr-Eddine Chérief-Abdellatif	Link	Link
Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism	Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu	Link	None
Streaming Coresets for Symmetric Tensor Factorization	Rachit Chhaya, Jayesh Choudhari, Anirban Dasgupta, Supratim Shit	Link	Link
On Coresets for Regularized Regression	Rachit Chhaya, Anirban Dasgupta, Supratim Shit	Link	Link
How to Solve Fair k-Center in Massive Data Models	Ashish Chiplunkar, Sagar Kale, Sivaramakrishnan Natarajan Ramamoorthy	Link	Link
Fair Generative Modeling via Weak Supervision	Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon	Link	Link
Encoding Musical Style with Transformer Autoencoders	Kristy Choi, Curtis Hawthorne, Ian Simon, Monica Dinculescu, Jesse Engel	Link	Link
k-means++: few more steps yield constant approximation	Davin Choo, Christoph Grunau, Julian Portmann, Vaclav Rozhon	Link	Link
Stochastic Flows and Geometric Optimization on the Orthogonal Group	Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamas Sarlos, Adrian Weller, Vikas Sindhwani	Link	Link
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels	Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama	Link	Link
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models	Amrita Roy Chowdhury, Theodoros Rekatsinas, Somesh Jha	Link	Link
Online Continual Learning from Imbalanced Data	Aristotelis Chrysakis, Marie-Francine Moens	Link	Link
Distance Metric Learning with Joint Representation Diversification	Xu Chu, Yang Lin, Yasha Wang, Xiting Wang, Hailong Yu, Xin Gao, Qi Tong	Link	Link
Semismooth Newton Algorithm for Efficient Projections onto $\ell_1, ∞$-norm Ball	Dejun Chu, Changshui Zhang, Shiliang Sun, Qing Tao	Link	Link
Estimating Generalization under Distribution Shifts via Domain-Invariant Representations	Ching-Yao Chuang, Antonio Torralba, Stefanie Jegelka	Link	Link
Scalable and Efficient Comparison-based Search without Features	Daniyar Chumbalov, Lucas Maystre, Matthias Grossglauser	Link	Link
Feature-map-level Online Adversarial Knowledge Distillation	Inseop Chung, Seonguk Park, Jangho Kim, Nojun Kwak	Link	Link
Teaching with Limited Information on the Learner’s Behaviour	Ferdinando Cicalese, Sergio Filho, Eduardo Laber, Marco Molinaro	Link	Link
Deep Divergence Learning	Hatice Kubra Cilingir, Rachel Manzelli, Brian Kulis	Link	Link
Model Fusion with Kullback-Leibler Divergence	Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon	Link	Link
Leveraging Procedural Generation to Benchmark Reinforcement Learning	Karl Cobbe, Chris Hesse, Jacob Hilton, John Schulman	Link	Link
Composable Sketches for Functions of Frequencies: Beyond the Worst Case	Edith Cohen, Ofir Geri, Rasmus Pagh	Link	Link
Healing Products of Gaussian Process Experts	Samuel Cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Deisenroth	Link	Link
On Efficient Low Distortion Ultrametric Embedding	Vincent Cohen-Addad, Karthik C. S., Guillaume Lagarde	Link	None
Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data	Benjamin Coleman, Richard Baraniuk, Anshumali Shrivastava	Link	Link
Word-Level Speech Recognition With a Letter to Word Encoder	Ronan Collobert, Awni Hannun, Gabriel Synnaeve	Link	Link
Boosting Frank-Wolfe by Chasing Gradients	Cyrille Combettes, Sebastian Pokutta	Link	Link
Learning Opinions in Social Networks	Vincent Conitzer, Debmalya Panigrahi, Hanrui Zhang	Link	Link
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows	Rob Cornish, Anthony Caterini, George Deligiannidis, Arnaud Doucet	Link	Link
Adaptive Region-Based Active Learning	Corinna Cortes, Giulia Desalvo, Claudio Gentile, Mehryar Mohri, Ningshan Zhang	Link	Link
Online Learning with Dependent Stochastic Feedback Graphs	Corinna Cortes, Giulia Desalvo, Claudio Gentile, Mehryar Mohri, Ningshan Zhang	Link	Link
Learnable Group Transform For Time-Series	Romain Cosentino, Behnaam Aazhang	Link	Link
DINO: Distributed Newton-Type Optimization Method	Rixon Crane, Fred Roosta	Link	Link
Causal Modeling for Fairness In Dynamical Systems	Elliot Creager, David Madras, Toniann Pitassi, Richard Zemel	Link	Link
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack	Francesco Croce, Matthias Hein	Link	Link
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks	Francesco Croce, Matthias Hein	Link	Link
Real-Time Optimisation for Online Learning in Auctions	Lorenzo Croissant, Marc Abeille, Clement Calauzenes	Link	Link
Privately detecting changes in unknown distributions	Rachel Cummings, Sara Krehbiel, Yuliia Lut, Wanrong Zhang	Link	Link
Flexible and Efficient Long-Range Planning Through Curious Exploration	Aidan Curtis, Minjian Xin, Dilip Arumugam, Kevin Feigelis, Daniel Yamins	Link	Link
Parameter-free, Dynamic, and Strongly-Adaptive Online Learning	Ashok Cutkosky	Link	None
Momentum Improves Normalized SGD	Ashok Cutkosky, Harsh Mehta	Link	Link
Supervised Quantile Normalization for Low Rank Matrix Factorization	Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, Jean-Philippe Vert	Link	Link
Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime	Stéphane D’Ascoli, Maria Refinetti, Giulio Biroli, Florent Krzakala	Link	Link
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games	Zhongxiang Dai, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Teck-Hua Ho	Link	Link
Scalable Deep Generative Modeling for Sparse Graphs	Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans	Link	Link
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse	Bin Dai, Ziyu Wang, David Wipf	Link	Link
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting	Niccolo Dalmasso, Rafael Izbicki, Ann Lee	Link	Link
Goodness-of-Fit Tests for Inhomogeneous Random Graphs	Soham Dan, Bhaswar B. Bhattacharya	Link	Link
Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification	Chen Dan, Yuting Wei, Pradeep Ravikumar	Link	Link
Adversarial Attacks on Probabilistic Autoregressive Forecasting Models	Raphaël Dang-Nhu, Gagandeep Singh, Pavol Bielik, Martin Vechev	Link	Link
Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors	Yehuda Dar, Paul Mayer, Lorenzo Luzi, Richard Baraniuk	Link	Link
Probing Emergent Semantics in Predictive Agents via Question Answering	Abhishek Das, Federico Carnevale, Hamza Merzic, Laura Rimell, Rosalia Schneider, Josh Abramson, Alden Hung, Arun Ahuja, Stephen Clark, Greg Wayne, Felix Hill	Link	Link
Low-Variance and Zero-Variance Baselines for Extensive-Form Games	Trevor Davis, Martin Schmid, Michael Bowling	Link	Link
Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction	Filipe De Avila Belbute-Peres, Thomas Economon, Zico Kolter	Link	Link
Representing Unordered Data Using Complex-Weighted Multiset Automata	Justin Debenedetto, David Chiang	Link	Link
An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm	Chris Decarolis, Mukul Ram, Seyed Esmaeili, Yu-Xiang Wang, Furong Huang	Link	Link
Gamification of Pure Exploration for Linear Bandits	Rémy Degenne, Pierre Menard, Xuedong Shang, Michal Valko	Link	Link
Structure Adaptive Algorithms for Stochastic Bandits	Rémy Degenne, Han Shao, Wouter Koolen	Link	Link
Randomly Projected Additive Gaussian Processes for Regression	Ian Delbridge, David Bindel, Andrew Gordon Wilson	Link	Link
Interpreting Robust Optimization via Adversarial Influence Functions	Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang	Link	Link
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC	Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin	Link	Link
Towards Understanding the Dynamics of the First-Order Adversaries	Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie Su	Link	Link
Robust Pricing in Dynamic Mechanism Design	Yuan Deng, Sebastien Lahaie, Vahab Mirrokni	Link	Link
A Swiss Army Knife for Minimax Optimal Transport	Sofien Dhouib, Ievgen Redko, Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban	Link	Link
Margin-aware Adversarial Domain Adaptation with Optimal Transport	Sofien Dhouib, Ievgen Redko, Carole Lartizien	Link	Link
Enhancing Simple Models by Exploiting What They Already Know	Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss	Link	Link
Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence	Lijun Ding, Yingjie Fei, Qiantong Xu, Chengrun Yang	Link	Link
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features	Liang Ding, Rui Tuo, Shahin Shahrampour	Link	Link
Layered Sampling for Robust Optimization Problems	Hu Ding, Zixiu Wang	Link	Link
Growing Adaptive Multi-hyperplane Machines	Nemanja Djuric, Zhuang Wang, Slobodan Vucetic	Link	Link
Inexact Tensor Methods with Dynamic Accuracies	Nikita Doikov, Yurii Nesterov	Link	Link
Provable Smoothness Guarantees for Black-Box Variational Inference	Justin Domke	Link	Link
Optimal Differential Privacy Composition for Exponential Mechanisms	Jinshuo Dong, David Durfee, Ryan Rogers	Link	Link
Multinomial Logit Bandit with Low Switching Cost	Kefan Dong, Yingkai Li, Qin Zhang, Yuan Zhou	Link	Link
Towards Adaptive Residual Network Training: A Neural-ODE Perspective	Chengyu Dong, Liyuan Liu, Zichao Li, Jingbo Shang	Link	Link
On the Expressivity of Neural Networks for Deep Reinforcement Learning	Kefan Dong, Yuping Luo, Tianhe Yu, Chelsea Finn, Tengyu Ma	Link	Link
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems	Zhe Dong, Bryan Seybold, Kevin Murphy, Hung Bui	Link	Link
Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms	Chaosheng Dong, Bo Zeng	Link	Link
The Complexity of Finding Stationary Points with Stochastic Gradient Descent	Yoel Drori, Ohad Shamir	Link	Link
Optimal Non-parametric Learning in Repeated Contextual Auctions with Strategic Buyer	Alexey Drutsa	Link	Link
Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders	Alexey Drutsa	Link	Link
NGBoost: Natural Gradient Boosting for Probabilistic Prediction	Tony Duan, Avati Anand, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler	Link	Link
Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation	Yaqi Duan, Zeyu Jia, Mengdi Wang	Link	None
Online Bayesian Moment Matching based SAT Solver Heuristics	Haonan Duan, Saeed Nejati, George Trimponias, Pascal Poupart, Vijay Ganesh	Link	Link
Familywise Error Rate Control by Interactive Unmasking	Boyan Duan, Aaditya Ramdas, Larry Wasserman	Link	Link
Cooperative Multi-Agent Bandits with Heavy Tails	Abhimanyu Dubey, Alex ‘Sandy’ Pentland	Link	Link
Kernel Methods for Cooperative Multi-Agent Contextual Bandits	Abhimanyu Dubey, Alex ‘Sandy’ Pentland	Link	Link
Optimization Theory for ReLU Neural Networks Trained with Normalization Layers	Yonatan Dukler, Quanquan Gu, Guido Montufar	Link	Link
Equivariant Neural Rendering	Emilien Dupont, Miguel Bautista Martin, Alex Colburn, Aditya Sankar, Josh Susskind, Qi Shan	Link	Link
On Contrastive Learning for Likelihood-free Inference	Conor Durkan, Iain Murray, George Papamakarios	Link	Link
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors	Michael Dusenberry, Ghassen Jerfel, Yeming Wen, Yian Ma, Jasper Snoek, Katherine Heller, Balaji Lakshminarayanan, Dustin Tran	Link	Link
Sparse Gaussian Processes with Spherical Harmonic Features	Vincent Dutordoir, Nicolas Durrande, James Hensman	Link	Link
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing	Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush Varshney	Link	Link
Self-Concordant Analysis of Frank-Wolfe Algorithms	Pavel Dvurechensky, Petr Ostroukhov, Kamil Safin, Shimrit Shtern, Mathias Staudigl	Link	Link
Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients	Ashley Edwards, Himanshu Sahni, Rosanne Liu, Jane Hung, Ankit Jain, Rui Wang, Adrien Ecoffet, Thomas Miconi, Charles Isbell, Jason Yosinski	Link	Link
Training Linear Neural Networks: Non-Local Convergence and Complexity Results	Armin Eftekhari	Link	Link
Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location	Rasheed El-Bouri, David Eyre, Peter Watkinson, Tingting Zhu, David Clifton	Link	Link
Decision Trees for Decision-Making under the Predict-then-Optimize Framework	Adam Elmachtoub, Jason Cheuk Nam Liang, Ryan Mcnellis	Link	Link
Revisiting Spatial Invariance with Low-Rank Local Connectivity	Gamaleldin Elsayed, Prajit Ramachandran, Jonathon Shlens, Simon Kornblith	Link	Link
Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks	Ahmed Taha Elthakeb, Prannoy Pilligundla, Fatemeh Mireshghallah, Alexander Cloninger, Hadi Esmaeilzadeh	Link	Link
Generalization Error of Generalized Linear Models in High Dimensions	Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson Fletcher	Link	Link
Parallel Algorithm for Non-Monotone DR-Submodular Maximization	Alina Ene, Huy Nguyen	Link	Link
Continuous Time Bayesian Networks with Clocks	Nicolai Engelmann, Dominik Linzner, Heinz Koeppl	Link	Link
Identifying Statistical Bias in Dataset Replication	Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry	Link	Link
Distributed Online Optimization over a Heterogeneous Network with Any-Batch Mirror Descent	Nima Eshraghi, Ben Liang	Link	Link
Rigging the Lottery: Making All Tickets Winners	Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen	Link	Link
Faster Graph Embeddings via Coarsening	Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang	Link	Link
Latent Bernoulli Autoencoder	Jiri Fajtl, Vasileios Argyriou, Dorothy Monekosso, Paolo Remagnino	Link	Link
Optimal Sequential Maximization: One Interview is Enough!	Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati	Link	Link
Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory	Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu	Link	Link
On hyperparameter tuning in general clustering problemsm	Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang	Link	Link
Online mirror descent and dual averaging: keeping pace in the dynamic case	Huang Fang, Nick Harvey, Victor Portella, Michael Friedlander	Link	Link
Stochastic Regret Minimization in Extensive-Form Games	Gabriele Farina, Christian Kroer, Tuomas Sandholm	Link	Link
Do GANs always have Nash equilibria?	Farzan Farnia, Asuman Ozdaglar	Link	Link
Growing Action Spaces	Gregory Farquhar, Laura Gustafson, Zeming Lin, Shimon Whiteson, Nicolas Usunier, Gabriel Synnaeve	Link	Link
Improved Optimistic Algorithms for Logistic Bandits	Louis Faury, Marc Abeille, Clement Calauzenes, Olivier Fercoq	Link	Link
Revisiting Fundamentals of Experience Replay	William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney	Link	Link
Learning with Multiple Complementary Labels	Lei Feng, Takuo Kaneko, Bo Han, Gang Niu, Bo An, Masashi Sugiyama	Link	Link
Global Concavity and Optimization in a Class of Dynamic Discrete Choice Models	Yiding Feng, Ekaterina Khmelnitskaya, Denis Nekipelov	Link	Link
The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation	Zhe Feng, David Parkes, Haifeng Xu	Link	Link
Accountable Off-Policy Evaluation With Kernel Bellman Statistics	Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu	Link	Link
Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data	Tamara Fernandez, Nicolas Rivera, Wenkai Xu, Arthur Gretton	Link	Link
Why Are Learned Indexes So Effective?	Paolo Ferragina, Fabrizio Lillo, Giorgio Vinciguerra	Link	Link
Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study	Tanner Fiez, Benjamin Chasnov, Lillian Ratliff	Link	Link
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?	Angelos Filos, Panagiotis Tigkas, Rowan Mcallister, Nicholas Rhinehart, Sergey Levine, Yarin Gal	Link	Link
How to Train Your Neural ODE: the World of Jacobian and Kinetic Regularization	Chris Finlay, Joern-Henrik Jacobsen, Levon Nurbekyan, Adam Oberman	Link	Link
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data	Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson	Link	Link
Information Particle Filter Tree: An Online Algorithm for POMDPs with Belief-Based Rewards on Continuous Domains	Johannes Fischer, Ömer Sahin Tas	Link	Link
Topic Modeling via Full Dependence Mixtures	Dan Fisher, Mark Kozdoba, Shie Mannor	Link	Link
Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles	Dylan Foster, Alexander Rakhlin	Link	Link
Logarithmic Regret for Adversarial Online Control	Dylan Foster, Max Simchowitz	Link	Link
p-Norm Flow Diffusion for Local Graph Clustering	Kimon Fountoulakis, Di Wang, Shenghao Yang	Link	Link
Stochastic Latent Residual Video Prediction	Jean-Yves Franceschi, Edouard Delasalles, Mickael Chen, Sylvain Lamprier, Patrick Gallinari	Link	Link
Leveraging Frequency Analysis for Deep Fake Image Recognition	Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, Thorsten Holz	Link	Link
Linear Mode Connectivity and the Lottery Ticket Hypothesis	Jonathan Frankle, Gintare Karolina Dziugaite, Daniel Roy, Michael Carbin	Link	Link
No-Regret and Incentive-Compatible Online Learning	Rupert Freeman, David Pennock, Chara Podimata, Jennifer Wortman Vaughan	Link	Link
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods	Daniel Fu, Mayee Chen, Frederic Sala, Sarah Hooper, Kayvon Fatahalian, Christopher Re	Link	Link
AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks	Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang Wang	Link	Link
Don’t Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript	Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui	Link	Link
DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths	Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan Yao	Link	Link
Approximation Guarantees of Local Search Algorithms via Localizability of Set Functions	Kaito Fujii	Link	Link
Accelerating the diffusion-based ensemble sampling by non-reversible dynamics	Futoshi Futami, Issei Sato, Masashi Sugiyama	Link	Link
Stochastic bandits with arm-dependent delays	Manegueu Anne Gael, Claire Vernade, Alexandra Carpentier, Michal Valko	Link	Link
Abstraction Mechanisms Predict Generalization in Deep Neural Networks	Alex Gain, Hava Siegelmann	Link	Link
A Free-Energy Principle for Representation Learning	Yansong Gao, Pratik Chaudhari	Link	Link
Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems?	Hongchang Gao, Heng Huang	Link	Link
Online Convex Optimization in the Random Order Model	Dan Garber, Gal Korcia, Kfir Levy	Link	Link
Symbolic Network: Generalized Neural Policies for Relational MDPs	Sankalp Garg, Aniket Bajpai, Mausam	Link	Link
Predicting deliberative outcomes	Vikas Garg, Tommi Jaakkola	Link	Link
Generalization and Representational Limits of Graph Neural Networks	Vikas Garg, Stefanie Jegelka, Tommi Jaakkola	Link	Link
Deep PQR: Solving Inverse Reinforcement Learning using Anchor Actions	Sinong Geng, Houssam Nassif, Carlos Manzanares, Max Reppen, Ronnie Sircar	Link	Link
Multilinear Latent Conditioning for Generating Unseen Attribute Combinations	Markos Georgopoulos, Grigorios Chrysos, Maja Pantic, Yannis Panagakis	Link	Link
Generalisation error in learning with random features and the hidden manifold model	Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mezard, Lenka Zdeborova	Link	Link
Black-Box Methods for Restoring Monotonicity	Evangelia Gergatsouli, Brendan Lucier, Christos Tzamos	Link	Link
Online Multi-Kernel Learning with Graph-Structured Feedback	Pouya M Ghari, Yanning Shen	Link	Link
Task-Oriented Active Perception and Planning in Environments with Partially Known Semantics	Mahsa Ghasemi, Erdem Bulgur, Ufuk Topcu	Link	Link
Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs	Amiremad Ghassami, Alan Yang, Negar Kiyavash, Kun Zhang	Link	Link
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead	Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh	Link	Link
Aligned Cross Entropy for Non-Autoregressive Machine Translation	Marjan Ghazvininejad, Vladimir Karpukhin, Luke Zettlemoyer, Omer Levy	Link	None
Gradient Temporal-Difference Learning with Regularized Corrections	Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White	Link	Link
A Distributional Framework For Data Valuation	Amirata Ghorbani, Michael Kim, James Zou	Link	Link
Fractal Gaussian Networks: A sparse random graph model based on Gaussian Multiplicative Chaos	Subhroshekhar Ghosh, Krishna Balasubramanian, Xiaochuan Yang	Link	Link
Representations for Stable Off-Policy Reinforcement Learning	Dibya Ghosh, Marc G. Bellemare	Link	Link
Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition	Alex Gittens, Kareem Aggour, Bülent Yener	Link	Link
One Size Fits All: Can We Train One Denoiser for All Noise Levels?	Abhiram Gnanasambandam, Stanley Chan	Link	None
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent	Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam Klivans	Link	Link
SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification	Tomer Golany, Kira Radinsky, Daniel Freedman	Link	Link
Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks	Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein	Link	Link
Towards a General Theory of Infinite-Width Limits of Neural Classifiers	Eugene Golikov	Link	Link
Differentially Private Set Union	Sivakanth Gopi, Pankaj Gulhane, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin	Link	Link
The continuous categorical: a novel simplex-valued exponential family	Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, John Cunningham	Link	Link
Automatic Reparameterisation of Probabilistic Programs	Maria Gorinova, Dave Moore, Matthew Hoffman	Link	Link
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions	Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Celi, Emma Brunskill, Finale Doshi-Velez	Link	Link
Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning	Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Shengchao Liu, Simon Blackburn, Karam Thomas, Connor Coley, Jian Tang, Sarath Chandar, Yoshua Bengio	Link	Link
Ordinal Non-negative Matrix Factorization for Recommendation	Olivier Gouvert, Thomas Oberlin, Cédric Févotte	Link	Link
PoWER-BERT: Accelerating BERT Inference via Progressive Word-vector Elimination	Saurabh Goyal, Anamitra Roy Choudhury, Saurabh Raje, Venkatesan Chakaravarthy, Yogish Sabharwal, Ashish Verma	Link	Link
PackIt: A Virtual Environment for Geometric Planning	Ankit Goyal, Jia Deng	Link	Link
DROCC: Deep Robust One-Class Classification	Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain	Link	Link
Scalable Gaussian Process Separation for Kernels with a Non-Stationary Phase	Jan Graßhoff, Alexandra Jankowski, Philipp Rostalski	Link	Link
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling	Will Grathwohl, Kuan-Chieh Wang, Joern-Henrik Jacobsen, David Duvenaud, Richard Zemel	Link	None
On the Iteration Complexity of Hypergradient Computation	Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil, Saverio Salzo	Link	Link
Robust Learning with the Hilbert-Schmidt Independence Criterion	Daniel Greenfeld, Uri Shalit	Link	Link
Monte-Carlo Tree Search as Regularized Policy Optimization	Jean-Bastien Grill, Florent Altché, Yunhao Tang, Thomas Hubert, Michal Valko, Ioannis Antonoglou, Remi Munos	Link	Link
Near-Tight Margin-Based Generalization Bounds for Support Vector Machines	Allan Grønlund, Lior Kamma, Kasper Green Larsen	Link	None
Implicit Geometric Regularization for Learning Shapes	Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, Yaron Lipman	Link	Link
Improving the Gating Mechanism of Recurrent Neural Networks	Albert Gu, Caglar Gulcehre, Thomas Paine, Matt Hoffman, Razvan Pascanu	Link	Link
Recurrent Hierarchical Topic-Guided RNN for Language Generation	Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou	Link	Link
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search	Yong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan	Link	Link
Certified Data Removal from Machine Learning Models	Chuan Guo, Tom Goldstein, Awni Hannun, Laurens Van Der Maaten	Link	Link
LTF: A Label Transformation Framework for Correcting Label Shift	Jiaxian Guo, Mingming Gong, Tongliang Liu, Kun Zhang, Dacheng Tao	Link	Link
Learning to Branch for Multi-Task Learning	Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht	Link	Link
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks	Zhishuai Guo, Mingrui Liu, Zhuoning Yuan, Li Shen, Wei Liu, Tianbao Yang	Link	Link
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning	Zhaohan Daniel Guo, Bernardo Avila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Remi Munos, Mohammad Gheshlaghi Azar	Link	Link
Accelerating Large-Scale Inference with Anisotropic Vector Quantization	Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, Sanjiv Kumar	Link	Link
Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data	Lan-Zhe Guo, Zhen-Yu Zhang, Yuan Jiang, Yu-Feng Li, Zhi-Hua Zhou	Link	Link
Neural Topic Modeling with Continual Lifelong Learning	Pankaj Gupta, Yatin Chaudhary, Thomas Runkler, Hinrich Schuetze	Link	Link
Multidimensional Shape Constraints	Maya Gupta, Erez Louidor, Oleksandr Mangylov, Nobu Morioka, Taman Narayan, Sen Zhao	Link	Link
Retrieval Augmented Language Model Pre-Training	Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, Mingwei Chang	Link	Link
Streaming Submodular Maximization under a k-Set System Constraint	Ran Haba, Ehsan Kazemi, Moran Feldman, Amin Karbasi	Link	Link
Let’s Agree to Agree: Neural Networks Share Classification Order on Real Datasets	Guy Hacohen, Leshem Choshen, Daphna Weinshall	Link	Link
Optimal approximation for unconstrained non-submodular minimization	Marwa El Halabi, Stefanie Jegelka	Link	Link
FedBoost: A Communication-Efficient Algorithm for Federated Learning	Jenny Hamer, Mehryar Mohri, Ananda Theertha Suresh	Link	Link
Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix	Insu Han, Haim Avron, Jinwoo Shin	Link	Link
DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D Structure Learning from Silhouette Images	Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker	Link	Link
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust	Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor Tsang, Masashi Sugiyama	Link	Link
Training Binary Neural Networks through Learning with Noisy Supervision	Kai Han, Yunhe Wang, Yixing Xu, Chunjing Xu, Enhua Wu, Chang Xu	Link	Link
Stochastic Subspace Cubic Newton Method	Filip Hanzely, Nikita Doikov, Yurii Nesterov, Peter Richtarik	Link	Link
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems	Filip Hanzely, Dmitry Kovalev, Peter Richtarik	Link	Link
Data Amplification: Instance-Optimal Property Estimation	Yi Hao, Alon Orlitsky	Link	Link
Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising	Xiaotian Hao, Zhaoqing Peng, Yi Ma, Guan Wang, Junqi Jin, Jianye Hao, Shan Chen, Rongquan Bai, Mingzhou Xie, Miao Xu, Zhenzhe Zheng, Chuan Yu, Han Li, Jian Xu, Kun Gai	Link	Link
Improving generalization by controlling label-noise information in neural network weights	Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan	Link	Link
A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits	Ramin Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu	Link	Link
Bayesian Graph Neural Networks with Adaptive Connection Sampling	Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian	Link	Link
CoMic: Complementary Task Learning & Mimicry for Reusable Skills	Leonard Hasenclever, Fabio Pardo, Raia Hadsell, Nicolas Heess, Josh Merel	Link	Link
Contrastive Multi-View Representation Learning on Graphs	Kaveh Hassani, Amir Hosein Khasahmadi	Link	Link
Nested Subspace Arrangement for Representation of Relational Data	Nozomi Hata, Shizuo Kaji, Akihiro Yoshida, Katsuki Fujisawa	Link	Link
The Tree Ensemble Layer: Differentiability meets Conditional Computation	Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder	Link	Link
Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation	Reinhard Heckel, Mahdi Soltanolkotabi	Link	Link
Hierarchically Decoupled Imitation For Morphological Transfer	Donald Hejna, Lerrel Pinto, Pieter Abbeel	Link	Link
Gradient-free Online Learning in Continuous Games with Delayed Rewards	Amélie Héliou, Panayotis Mertikopoulos, Zhengyuan Zhou	Link	Link
Data-Efficient Image Recognition with Contrastive Predictive Coding	Olivier Henaff	Link	Link
Minimax Rate for Learning From Pairwise Comparisons in the BTL Model	Julien Hendrickx, Alex Olshevsky, Venkatesh Saligrama	Link	Link
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization	Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck, Francis Bach, Laurent Massoulie	Link	Link
Cost-Effective Interactive Attention Learning with Neural Attention Processes	Jay Heo, Junhyeon Park, Hyewon Jeong, Kwang Joon Kim, Juho Lee, Eunho Yang, Sung Ju Hwang	Link	Link
Likelihood-free MCMC with Amortized Approximate Ratio Estimators	Joeri Hermans, Volodimir Begy, Gilles Louppe	Link	Link
Towards Non-Parametric Drift Detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD)	Fabian Hinder, André Artelt, Barbara Hammer	Link	Link
Optimization and Analysis of the pAp@k Metric for Recommender Systems	Gaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain	Link	Link
Optimizing Dynamic Structures with Bayesian Generative Search	Minh Hoang, Carleton Kingsford	Link	None
Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion	Nghia Hoang, Thanh Lam, Bryan Kian Hsiang Low, Patrick Jaillet	Link	Link
Parameterized Rate-Distortion Stochastic Encoder	Quan Hoang, Trung Le, Dinh Phung	Link	Link
Topologically Densified Distributions	Christoph Hofer, Florian Graf, Marc Niethammer, Roland Kwitt	Link	Link
Graph Filtration Learning	Christoph Hofer, Florian Graf, Bastian Rieck, Marc Niethammer, Roland Kwitt	Link	Link
Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics	Matthew Hoffman, Yian Ma	Link	Link
Learning Mixtures of Graphs from Epidemic Cascades	Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis	Link	Link
Set Functions for Time Series	Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten Borgwardt	Link	Link
Lifted Disjoint Paths with Application in Multiple Object Tracking	Andrea Hornakova, Roberto Henschel, Bodo Rosenhahn, Paul Swoboda	Link	Link
Infinite attention: NNGP and NTK for deep attention networks	Jiri Hron, Yasaman Bahri, Jascha Sohl-Dickstein, Roman Novak	Link	Link
The Non-IID Data Quagmire of Decentralized Machine Learning	Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phillip Gibbons	Link	Link
“Other-Play” for Zero-Shot Coordination	Hengyuan Hu, Adam Lerer, Alex Peysakhovich, Jakob Foerster	Link	None
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalisation	Junjie Hu, Sebastian Ruder, Aditya Siddhant, Graham Neubig, Orhan Firat, Melvin Johnson	Link	Link
Momentum-Based Policy Gradient Methods	Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang	Link	Link
From Importance Sampling to Doubly Robust Policy Gradient	Jiawei Huang, Nan Jiang	Link	Link
Evaluating Lossy Compression Rates of Deep Generative Models	Sicong Huang, Alireza Makhzani, Yanshuai Cao, Roger Grosse	Link	Link
One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control	Wenlong Huang, Igor Mordatch, Deepak Pathak	Link	Link
Communication-Efficient Distributed PCA by Riemannian Optimization	Long-Kai Huang, Sinno Pan	Link	Link
Improving Transformer Optimization Through Better Initialization	Xiao Shi Huang, Felipe Perez, Jimmy Ba, Maksims Volkovs	Link	Link
More Information Supervised Probabilistic Deep Face Embedding Learning	Ying Huang, Shangfeng Qiu, Wenwei Zhang, Xianghui Luo, Jinzhuo Wang	Link	None
Generating Programmatic Referring Expressions via Program Synthesis	Jiani Huang, Calvin Smith, Osbert Bastani, Rishabh Singh, Aws Albarghouthi, Mayur Naik	Link	Link
InstaHide: Instance-hiding Schemes for Private Distributed Learning	Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora	Link	Link
Accelerated Stochastic Gradient-free and Projection-free Methods	Feihu Huang, Lue Tao, Songcan Chen	Link	Link
Deep Graph Random Process for Relational-Thinking-Based Speech Recognition	Hengguan Huang, Fuzhao Xue, Hao Wang, Ye Wang	Link	Link
Dynamics of Deep Neural Networks and Neural Tangent Hierarchy	Jiaoyang Huang, Horng-Tzer Yau	Link	None
Curvature-corrected learning dynamics in deep neural networks	Dongsung Huh	Link	Link
Multigrid Neural Memory	Tri Huynh, Michael Maire, Matthew Walter	Link	Link
Meta-Learning with Shared Amortized Variational Inference	Ekaterina Iakovleva, Jakob Verbeek, Karteek Alahari	Link	Link
Linear Lower Bounds and Conditioning of Differentiable Games	Adam Ibrahim, Waı̈ss Azizian, Gauthier Gidel, Ioannis Mitliagkas	Link	Link
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance	Yasutoshi Ida, Sekitoshi Kanai, Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima	Link	Link
Do We Need Zero Training Loss After Achieving Zero Training Error?	Takashi Ishida, Ikko Yamane, Tomoya Sakai, Gang Niu, Masashi Sugiyama	Link	Link
Semi-Supervised Learning with Normalizing Flows	Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Gordon Wilson	Link	Link
Implicit Regularization of Random Feature Models	Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clement Hongler, Franck Gabriel	Link	Link
Correlation Clustering with Asymmetric Classification Errors	Jafar Jafarov, Sanchit Kalhan, Konstantin Makarychev, Yury Makarychev	Link	None
Optimal Robust Learning of Discrete Distributions from Batches	Ayush Jain, Alon Orlitsky	Link	Link
Generalization to New Actions in Reinforcement Learning	Ayush Jain, Andrew Szot, Joseph Lim	Link	Link
Tails of Lipschitz Triangular Flows	Priyank Jaini, Ivan Kobyzev, Yaoliang Yu, Marcus Brubaker	Link	Link
Learning Portable Representations for High-Level Planning	Steven James, Benjamin Rosman, George Konidaris	Link	Link
Debiased Sinkhorn barycenters	Hicham Janati, Marco Cuturi, Alexandre Gramfort	Link	Link
Parametric Gaussian Process Regressors	Martin Jankowiak, Geoff Pleiss, Jacob Gardner	Link	Link
Inverse Active Sensing: Modeling and Understanding Timely Decision-Making	Daniel Jarrett, Mihaela Van Der Schaar	Link	Link
Source Separation with Deep Generative Priors	Vivek Jayaram, John Thickstun	Link	Link
Extra-gradient with player sampling for faster convergence in n-player games	Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna	Link	Link
T-GD: Transferable GAN-generated Images Detection Framework	Hyeonseong Jeon, Young Oh Bang, Junyaup Kim, Simon Woo	Link	Link
History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms	Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin Liang	Link	Link
Information-Theoretic Local Minima Characterization and Regularization	Zhiwei Jia, Hao Su	Link	Link
Optimizing Black-box Metrics with Adaptive Surrogates	Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan, Mahdi Milani Fard, Maya Gupta	Link	Link
BINOCULARS for efficient, nonmyopic sequential experimental design	Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett	Link	Link
Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels	Lu Jiang, Di Huang, Mason Liu, Weilong Yang	Link	Link
Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation	Xiang Jiang, Qicheng Lao, Stan Matwin, Mohammad Havaei	Link	Link
Associative Memory in Iterated Overparameterized Sigmoid Autoencoders	Yibo Jiang, Cengiz Pehlevan	Link	Link
Hierarchical Generation of Molecular Graphs using Structural Motifs	Wengong Jin, Dr.Regina Barzilay, Tommi Jaakkola	Link	Link
Multi-Objective Molecule Generation using Interpretable Substructures	Wengong Jin, Dr.Regina Barzilay, Tommi Jaakkola	Link	Link
Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition	Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu	Link	Link
Reward-Free Exploration for Reinforcement Learning	Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu	Link	Link
What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?	Chi Jin, Praneeth Netrapalli, Michael Jordan	Link	Link
Efficiently Solving MDPs with Stochastic Mirror Descent	Yujia Jin, Aaron Sidford	Link	Link
Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising Model	Ying Jin, Zhaoran Wang, Junwei Lu	Link	Link
AdaScale SGD: A User-Friendly Algorithm for Distributed Training	Tyler Johnson, Pulkit Agrawal, Haijie Gu, Carlos Guestrin	Link	Link
Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization	Rie Johnson, Tong Zhang	Link	Link
On Relativistic f-Divergences	Alexia Jolicoeur-Martineau	Link	Link
Fair k-Centers via Maximum Matching	Matthew Jones, Huy Nguyen, Thy Nguyen	Link	Link
Being Bayesian about Categorical Probability	Taejong Joo, Uijung Chung, Min-Gwan Seo	Link	Link
Evaluating the Performance of Reinforcement Learning Algorithms	Scott Jordan, Yash Chandak, Daniel Cohen, Mengxue Zhang, Philip Thomas	Link	Link
Stochastic Differential Equations with Variational Wishart Diffusions	Martin Jørgensen, Marc Deisenroth, Hugh Salimbeni	Link	Link
A simpler approach to accelerated optimization: iterative averaging meets optimism	Pooria Joulani, Anant Raj, Andras Gyorgy, Csaba Szepesvari	Link	Link
Sets Clustering	Ibrahim Jubran, Murad Tukan, Alaa Maalouf, Dan Feldman	Link	Link
Distribution Augmentation for Generative Modeling	Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever	Link	Link
Sub-Goal Trees a Framework for Goal-Based Reinforcement Learning	Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar	Link	Link
Partial Trace Regression and Low-Rank Kraus Decomposition	Hachem Kadri, Stephane Ayache, Riikka Huusari, Alain Rakotomamonjy, Ralaivola Liva	Link	Link
Strategyproof Mean Estimation from Multiple-Choice Questions	Anson Kahng, Gregory Kehne, Ariel Procaccia	Link	Link
Variational Autoencoders with Riemannian Brownian Motion Priors	Dimitrios Kalatzis, David Eklund, Georgios Arvanitidis, Soren Hauberg	Link	Link
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training	Nathan Kallus	Link	Link
Double Reinforcement Learning for Efficient and Robust Off-Policy Evaluation	Nathan Kallus, Masatoshi Uehara	Link	Link
Statistically Efficient Off-Policy Policy Gradients	Nathan Kallus, Masatoshi Uehara	Link	Link
On the Power of Compressed Sensing with Generative Models	Akshay Kamath, Eric Price, Sushrut Karmalkar	Link	Link
Learning and Evaluating Contextual Embedding of Source Code	Aditya Kanade, Petros Maniatis, Gogul Balakrishnan, Kensen Shi	Link	Link
Operation-Aware Soft Channel Pruning using Differentiable Masks	Minsoo Kang, Bohyung Han	Link	None
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning	Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank Reddi, Sebastian Stich, Ananda Theertha Suresh	Link	Link
Non-autoregressive Machine Translation with Disentangled Context Transformer	Jungo Kasai, James Cross, Marjan Ghazvininejad, Jiatao Gu	Link	Link
Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention	Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, François Fleuret	Link	Link
Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space	Keizo Kato, Jing Zhou, Tomotake Sasaki, Akira Nakagawa	Link	Link
Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations	Stephen Keeley, David Zoltowski, Yiyi Yu, Spencer Smith, Jonathan Pillow	Link	None
Quantum Expectation-Maximization for Gaussian mixture models	Iordanis Kerenidis, Alessandro Luongo, Anupam Prakash	Link	Link
Differentiable Likelihoods for Fast Inversion of ’Likelihood-Free’ Dynamical Systems	Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig	Link	Link
Feature Noise Induces Loss Discrepancy Across Groups	Fereshte Khani, Percy Liang	Link	Link
Entropy Minimization In Emergent Languages	Eugene Kharitonov, Rahma Chaabouni, Diane Bouchacourt, Marco Baroni	Link	Link
Private Outsourced Bayesian Optimization	Dmitrii Kharkovskii, Zhongxiang Dai, Bryan Kian Hsiang Low	Link	Link
What can I do here? A Theory of Affordances in Reinforcement Learning	Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, David Abel, Doina Precup	Link	Link
Uniform Convergence of Rank-weighted Learning	Justin Khim, Liu Leqi, Adarsh Prasad, Pradeep Ravikumar	Link	Link
FACT: A Diagnostic for Group Fairness Trade-offs	Joon Sik Kim, Jiahao Chen, Ameet Talwalkar	Link	Link
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup	Jang-Hyun Kim, Wonho Choo, Hyun Oh Song	Link	Link
Domain Adaptive Imitation Learning	Kuno Kim, Yihong Gu, Jiaming Song, Shengjia Zhao, Stefano Ermon	Link	Link
Variational Inference for Sequential Data with Future Likelihood Estimates	Geon-Hyeong Kim, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim	Link	Link
Active World Model Learning with Progress Curiosity	Kuno Kim, Megumi Sano, Julian De Freitas, Nick Haber, Daniel Yamins	Link	Link
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation	Steven Kleinegesse, Michael U. Gutmann	Link	Link
Optimal Continual Learning has Perfect Memory and is NP-hard	Jeremias Knoblauch, Hisham Husain, Tom Diethe	Link	Link
Concept Bottleneck Models	Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang	Link	Link
Learning Similarity Metrics for Numerical Simulations	Georg Kohl, Kiwon Um, Nils Thuerey	Link	Link
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities	Jonas Köhler, Leon Klein, Frank Noe	Link	Link
Online Learning for Active Cache Synchronization	Andrey Kolobov, Sebastien Bubeck, Julian Zimmert	Link	Link
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates	Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian Stich	Link	Link
Meta-learning for Mixed Linear Regression	Weihao Kong, Raghav Somani, Zhao Song, Sham Kakade, Sewoong Oh	Link	Link
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates	Lingkai Kong, Jimeng Sun, Chao Zhang	Link	Link
On the Sample Complexity of Adversarial Multi-Source PAC Learning	Nikola Konstantinov, Elias Frantar, Dan Alistarh, Christoph Lampert	Link	Link
Asynchronous Coagent Networks	James Kostas, Chris Nota, Philip Thomas	Link	Link
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks	Agustinus Kristiadi, Matthias Hein, Philipp Hennig	Link	Link
A Sequential Self Teaching Approach for Improving Generalization in Sound Event Recognition	Anurag Kumar, Vamsi Ithapu	Link	Link
Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness	Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi	Link	Link
Understanding Self-Training for Gradual Domain Adaptation	Ananya Kumar, Tengyu Ma, Percy Liang	Link	Link
On Implicit Regularization in $β$-VAEs	Abhishek Kumar, Ben Poole	Link	Link
Problems with Shapley-value-based explanations as feature importance measures	I. Elizabeth Kumar, Suresh Venkatasubramanian, Carlos Scheidegger, Sorelle Friedler	Link	None
Efficient Identification in Linear Structural Causal Models with Auxiliary Cutsets	Daniel Kumor, Carlos Cinelli, Elias Bareinboim	Link	None
Two Routes to Scalable Credit Assignment without Weight Symmetry	Daniel Kunin, Aran Nayebi, Javier Sagastuy-Brena, Surya Ganguli, Jonathan Bloom, Daniel Yamins	Link	Link
Online Dense Subgraph Discovery via Blurred-Graph Feedback	Yuko Kuroki, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama	Link	Link
Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural Networks	Mark Kurtz, Justin Kopinsky, Rati Gelashvili, Alexander Matveev, John Carr, Michael Goin, William Leiserson, Sage Moore, Nir Shavit, Dan Alistarh	Link	None
Soft Threshold Weight Reparameterization for Learnable Sparsity	Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham Kakade, Ali Farhadi	Link	Link
Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics	Arsenii Kuznetsov, Pavel Shvechikov, Alexander Grishin, Dmitry Vetrov	Link	Link
Principled learning method for Wasserstein distributionally robust optimization with local perturbations	Yongchan Kwon, Wonyoung Kim, Joong-Ho Won, Myunghee Cho Paik	Link	Link
Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions	Prashanth L.A., Krishna Jagannathan, Ravi Kolla	Link	None
Optimal Randomized First-Order Methods for Least-Squares Problems	Jonathan Lacotte, Mert Pilanci	Link	Link
Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses	Pierre Laforgue, Alex Lambert, Luc Brogat-Motte, Florence D’Alché-Buc	Link	Link
Recht-Re Noncommutative Arithmetic-Geometric Mean Conjecture is False	Zehua Lai, Lek-Heng Lim	Link	Link
Bidirectional Model-based Policy Optimization	Hang Lai, Jian Shen, Weinan Zhang, Yong Yu	Link	Link
Robust and Stable Black Box Explanations	Himabindu Lakkaraju, Nino Arsov, Osbert Bastani	Link	Link
CURL: Contrastive Unsupervised Representations for Reinforcement Learning	Michael Laskin, Aravind Srinivas, Pieter Abbeel	Link	Link
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks	Fabian Latorre, Paul Rolland, Nadav Hallak, Volkan Cevher	Link	Link
Learning with Good Feature Representations in Bandits and in RL with a Generative Model	Tor Lattimore, Csaba Szepesvari, Gellert Weisz	Link	Link
Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization	Hien Le, Nicolas Gillis, Panagiotis Patrinos	Link	Link
Self-Attentive Associative Memory	Hung Le, Truyen Tran, Svetha Venkatesh	Link	Link
Causal Effect Identifiability under Partial-Observability	Sanghack Lee, Elias Bareinboim	Link	None
Estimating Model Uncertainty of Neural Networks in Sparse Information Form	Jongseok Lee, Matthias Humt, Jianxiang Feng, Rudolph Triebel	Link	Link
Self-supervised Label Augmentation via Input Transformations	Hankook Lee, Sung Ju Hwang, Jinwoo Shin	Link	Link
Batch Reinforcement Learning with Hyperparameter Gradients	Byungjun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim	Link	Link
Accelerated Message Passing for Entropy-Regularized MAP Inference	Jonathan Lee, Aldo Pacchiano, Peter Bartlett, Michael Jordan	Link	Link
Learning Compound Tasks without Task-specific Knowledge via Imitation and Self-supervised Learning	Sang-Hyun Lee, Seung-Woo Seo	Link	Link
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning	Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin	Link	Link
Temporal Phenotyping using Deep Predictive Clustering of Disease Progression	Changhee Lee, Mihaela Van Der Schaar	Link	Link
Tensor denoising and completion based on ordinal observations	Chanwoo Lee, Miaoyan Wang	Link	Link
Analytic Marching: An Analytic Meshing Solution from Deep Implicit Surface Networks	Jiabao Lei, Kui Jia	Link	Link
SGD Learns One-Layer Networks in WGANs	Qi Lei, Jason Lee, Alex Dimakis, Constantinos Daskalakis	Link	Link
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent	Yunwen Lei, Yiming Ying	Link	Link
Learning Quadratic Games on Networks	Yan Leng, Xiaowen Dong, Junfeng Wu, Alex Pentland	Link	Link
ACFlow: Flow Models for Arbitrary Conditional Likelihoods	Yang Li, Shoaib Akbar, Junier Oliva	Link	Link
Manifold Identification for Ultimately Communication-Efficient Distributed Optimization	Yu-Sheng Li, Wei-Lin Chiang, Ching-Pei Lee	Link	Link
Neural Architecture Search in A Proxy Validation Loss Landscape	Yanxi Li, Minjing Dong, Yunhe Wang, Chang Xu	Link	Link
PENNI: Pruned Kernel Sharing for Efficient CNN Inference	Shiyu Li, Edward Hanson, Hai Li, Yiran Chen	Link	Link
Implicit Euler Skip Connections: Enhancing Adversarial Robustness via Numerical Stability	Mingjie Li, Lingshen He, Zhouchen Lin	Link	Link
Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning	Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song-Chun Zhu	Link	Link
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization	Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtarik	Link	Link
On the Relation between Quality-Diversity Evaluation and Distribution-Fitting Goal in Text Generation	Jianing Li, Yanyan Lan, Jiafeng Guo, Xueqi Cheng	Link	Link
Latent Space Factorisation and Manipulation via Matrix Subspace Projection	Xiao Li, Chenghua Lin, Ruizhe Li, Chaozheng Wang, Frank Guerin	Link	Link
Visual Grounding of Learned Physical Models	Yunzhu Li, Toru Lin, Kexin Yi, Daniel Bear, Daniel Yamins, Jiajun Wu, Joshua Tenenbaum, Antonio Torralba	Link	None
Learning from Irregularly-Sampled Time Series: A Missing Data Perspective	Steven Cheng-Xian Li, Benjamin Marlin	Link	Link
Evolutionary Topology Search for Tensor Network Decomposition	Chao Li, Zhun Sun	Link	Link
Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers	Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joey Gonzalez	Link	Link
Almost Tune-Free Variance Reduction	Bingcong Li, Lingda Wang, Georgios B. Giannakis	Link	Link
Nearly Linear Row Sampling Algorithm for Quantile Regression	Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang	Link	Link
Temporal Logic Point Processes	Shuang Li, Lu Wang, Ruizhi Zhang, Xiaofu Chang, Xuqin Liu, Yao Xie, Yuan Qi, Le Song	Link	Link
Input-Sparsity Low Rank Approximation in Schatten Norm	Yi Li, David Woodruff	Link	Link
RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr	Xingjian Li, Haoyi Xiong, Haozhe An, Cheng-Zhong Xu, Dejing Dou	Link	Link
On a projective ensemble approach to two sample test for equality of distributions	Zhimei Li, Yaowu Zhang	Link	Link
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation	Jian Liang, Dapeng Hu, Jiashi Feng	Link	Link
Variable Skipping for Autoregressive Range Density Estimation	Eric Liang, Zongheng Yang, Ion Stoica, Pieter Abbeel, Yan Duan, Peter Chen	Link	Link
Adaptive Droplet Routing in Digital Microfluidic Biochips Using Deep Reinforcement Learning	Tung-Che Liang, Zhanwei Zhong, Yaas Bigdeli, Tsung-Yi Ho, Krishnendu Chakrabarty, Richard Fair	Link	Link
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation	Jae Hyun Lim, Aaron Courville, Christopher Pal, Chin-Wei Huang	Link	Link
Hierarchical Verification for Adversarial Robustness	Cong Han Lim, Raquel Urtasun, Ersin Yumer	Link	Link
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems	Tianyi Lin, Chi Jin, Michael Jordan	Link	Link
Extrapolation for Large-batch Training in Deep Learning	Tao Lin, Lingjing Kong, Sebastian Stich, Martin Jaggi	Link	Link
On the Theoretical Properties of the Network Jackknife	Qiaohui Lin, Robert Lunde, Purnamrita Sarkar	Link	Link
Handling the Positive-Definite Constraint in the Bayesian Learning Rule	Wu Lin, Mark Schmidt, Mohammad Emtiyaz Khan	Link	Link
InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs	Zinan Lin, Kiran Thekumparampil, Giulia Fanti, Sewoong Oh	Link	Link
Improving Generative Imagination in Object-Centric World Models	Zhixuan Lin, Yi-Fu Wu, Skand Peri, Bofeng Fu, Jindong Jiang, Sungjin Ahn	Link	Link
Generalized and Scalable Optimal Sparse Decision Trees	Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo Seltzer	Link	Link
Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games	Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael Jordan	Link	Link
Time-aware Large Kernel Convolutions	Vasileios Lioutas, Yuhong Guo	Link	Link
Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling	Yao Liu, Pierre-Luc Bacon, Emma Brunskill	Link	Link
Sparse Shrunk Additive Models	Guodong Liu, Hong Chen, Heng Huang	Link	Link
Boosting Deep Neural Network Efficiency with Dual-Module Inference	Liu Liu, Lei Deng, Zhaodong Chen, Yuke Wang, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie	Link	Link
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors	Zhaoqiang Liu, Selwyn Gomes, Avtansh Tiwari, Jonathan Scarlett	Link	Link
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates	Yang Liu, Hongyi Guo	Link	Link
An Imitation Learning Approach for Cache Replacement	Evan Liu, Milad Hashemi, Kevin Swersky, Parthasarathy Ranganathan, Junwhan Ahn	Link	Link
Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits	Xi Liu, Ping-Chun Hsieh, Yu Heng Hung, Anirban Bhattacharya, P. Kumar	Link	Link
Hallucinative Topological Memory for Zero-Shot Visual Planning	Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar	Link	Link
A Chance-Constrained Generative Framework for Sequence Optimization	Xianggen Liu, Qiang Liu, Sen Song, Jian Peng	Link	Link
Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks	Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O’Reilly	Link	Link
Median Matrix Completion: from Embarrassment to Optimality	Weidong Liu, Xiaojun Mao, Raymond K. W. Wong	Link	Link
A Generic First-Order Algorithmic Framework for Bi-Level Programming Beyond Lower-Level Singleton	Risheng Liu, Pan Mu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang	Link	Link
Learning Deep Kernels for Non-Parametric Two-Sample Tests	Feng Liu, Wenkai Xu, Jie Lu, Guangquan Zhang, Arthur Gretton, D.J. Sutherland	Link	Link
Learning to Encode Position for Transformer with Continuous Dynamical Model	Xuanqing Liu, Hsiang-Fu Yu, Inderjit Dhillon, Cho-Jui Hsieh	Link	Link
Finding trainable sparse networks through Neural Tangent Transfer	Tianlin Liu, Friedemann Zenke	Link	Link
Weakly-Supervised Disentanglement Without Compromises	Francesco Locatello, Ben Poole, Gunnar Raetsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen	Link	Link
Too Relaxed to Be Fair	Michael Lohaus, Michael Perrot, Ulrike Von Luxburg	Link	Link
Stochastic Hamiltonian Gradient Methods for Smooth Games	Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas	Link	Link
Error Estimation for Sketched SVD via the Bootstrap	Miles Lopes, N. Benjamin Erichson, Michael Mahoney	Link	Link
Differentiating through the Fréchet Mean	Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Ser-Nam Lim, Christopher De Sa	Link	Link
Working Memory Graphs	Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht	Link	Link
Moniqua: Modulo Quantized Communication in Decentralized SGD	Yucheng Lu, Christopher De Sa	Link	Link
A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth	Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying	Link	Link
Countering Language Drift with Seeded Iterated Learning	Yuchen Lu, Soumye Singhal, Florian Strub, Aaron Courville, Olivier Pietquin	Link	Link
Does label smoothing mitigate label noise?	Michal Lukasik, Srinadh Bhojanapalli, Aditya Menon, Sanjiv Kumar	Link	Link
Improved Communication Cost in Distributed PageRank Computation – A Theoretical Study	Siqiang Luo	Link	None
Progressive Graph Learning for Open-Set Domain Adaptation	Yadan Luo, Zijian Wang, Zi Huang, Mahsa Baktashmotlagh	Link	Link
Adversarial Nonnegative Matrix Factorization	Lei Luo, Yanfu Zhang, Heng Huang	Link	Link
Learning Algebraic Multigrid Using Graph Neural Networks	Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh	Link	Link
Progressive Identification of True Labels for Partial-Label Learning	Jiaqi Lv, Miao Xu, Lei Feng, Gang Niu, Xin Geng, Masashi Sugiyama	Link	Link
Bandits with Adversarial Scaling	Thodoris Lykouris, Vahab Mirrokni, Renato Paes Leme	Link	Link
Efficient Continuous Pareto Exploration in Multi-Task Learning	Pingchuan Ma, Tao Du, Wojciech Matusik	Link	Link
Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space	Yingyi Ma, Vignesh Ganapathiraman, Yaoliang Yu, Xinhua Zhang	Link	Link
Normalized Loss Functions for Deep Learning with Noisy Labels	Xingjun Ma, Hanxun Huang, Yisen Wang, Simone Romano, Sarah Erfani, James Bailey	Link	Link
Quadratically Regularized Subgradient Methods for Weakly Convex Optimization with Weakly Convex Constraints	Runchao Ma, Qihang Lin, Tianbao Yang	Link	Link
Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle	Shaocong Ma, Yi Zhou	Link	Link
Adversarial Neural Pruning with Latent Vulnerability Suppression	Divyam Madaan, Jinwoo Shin, Sung Ju Hwang	Link	Link
Individual Fairness for k-Clustering	Sepideh Mahabadi, Ali Vakilian	Link	Link
Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto Optimization	Debabrata Mahapatra, Vaibhav Rajan	Link	Link
How recurrent networks implement contextual processing in sentiment analysis	Niru Maheswaranathan, David Sussillo	Link	Link
Anderson Acceleration of Proximal Gradient Methods	Vien Mai, Mikael Johansson	Link	Link
Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization	Vien Mai, Mikael Johansson	Link	Link
Adversarial Robustness Against the Union of Multiple Perturbation Models	Pratyush Maini, Eric Wong, Zico Kolter	Link	Link
Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination	Somdeb Majumdar, Shauharda Khadka, Santiago Miret, Stephen Mcaleer, Kagan Tumer	Link	Link
Estimation of Bounds on Potential Outcomes For Decision Making	Maggie Makar, Fredrik Johansson, John Guttag, David Sontag	Link	Link
Optimal transport mapping via input convex neural networks	Ashok Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason Lee	Link	Link
Proving the Lottery Ticket Hypothesis: Pruning is All You Need	Eran Malach, Gilad Yehudai, Shai Shalev-Schwartz, Ohad Shamir	Link	Link
From Local SGD to Local Fixed-Point Methods for Federated Learning	Grigory Malinovskiy, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtarik	Link	Link
Adaptive Gradient Descent without Descent	Yura Malitsky, Konstantin Mishchenko	Link	Link
Emergence of Separable Manifolds in Deep Language Representations	Jonathan Mamou, Hang Le, Miguel Del Rio, Cory Stephenson, Hanlin Tang, Yoon Kim, Sueyeon Chung	Link	Link
Adaptive Adversarial Multi-task Representation Learning	Yuren Mao, Weiwei Liu, Xuemin Lin	Link	Link
On Learning Sets of Symmetric Elements	Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya	Link	Link
Stochastically Dominant Distributional Reinforcement Learning	John Martin, Michal Lyskawinski, Xiaohu Li, Brendan Englot	Link	Link
Minimax Pareto Fairness: A Multi Objective Perspective	Natalia Martinez, Martin Bertran, Guillermo Sapiro	Link	Link
Predictive Multiplicity in Classification	Charles Marx, Flavio Calmon, Berk Ustun	Link	Link
Adding seemingly uninformative labels helps in low data regimes	Christos Matsoukas, Albert Bou Hernandez, Yue Liu, Karin Dembrower, Gisele Miranda, Emir Konuk, Johan Fredin Haslum, Athanasios Zouzos, Peter Lindholm, Fredrik Strand, Kevin Smith	Link	Link
Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations	Robert Mattila, Cristian Rojas, Eric Moulines, Vikram Krishnamurthy, Bo Wahlberg	Link	None
On Approximate Thompson Sampling with Langevin Algorithms	Eric Mazumdar, Aldo Pacchiano, Yian Ma, Michael Jordan, Peter Bartlett	Link	Link
Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification	Hongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner	Link	Link
On the Global Convergence Rates of Softmax Policy Gradient Methods	Jincheng Mei, Chenjun Xiao, Csaba Szepesvari, Dale Schuurmans	Link	Link
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM	Kunal Menda, Jean De Becdelievre, Jayesh Gupta, Ilan Kroo, Mykel Kochenderfer, Zachary Manchester	Link	Link
Randomized Block-Diagonal Preconditioning for Parallel Learning	Celestine Mendler-Dünner, Aurelien Lucchi	Link	Link
Training Binary Neural Networks using the Bayesian Learning Rule	Xiangming Meng, Roman Bachmann, Mohammad Emtiyaz Khan	Link	Link
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning	Alberto Maria Metelli, Flavio Mazzolini, Lorenzo Bisi, Luca Sabbioni, Marcello Restelli	Link	Link
The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture	Francesca Mignacco, Florent Krzakala, Yue Lu, Pierfrancesco Urbani, Lenka Zdeborova	Link	Link
Projective Preferential Bayesian Optimization	Petrus Mikkola, Milica Todorović, Jari Järvi, Patrick Rinke, Samuel Kaski	Link	Link
VideoOneNet: Bidirectional Convolutional Recurrent OneNet with Trainable Data Steps for Video Processing	Zoltán Milacski, Barnabas Poczos, Andras Lorincz	Link	Link
The Effect of Natural Distribution Shift on Question Answering Models	John Miller, Karl Krauth, Benjamin Recht, Ludwig Schmidt	Link	Link
Strategic Classification is Causal Modeling in Disguise	John Miller, Smitha Milli, Moritz Hardt	Link	Link
Automatic Shortcut Removal for Self-Supervised Representation Learning	Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen	Link	Link
Learning Reasoning Strategies in End-to-End Differentiable Proving	Pasquale Minervini, Sebastian Riedel, Pontus Stenetorp, Edward Grefenstette, Tim Rocktäschel	Link	Link
Coresets for Data-efficient Training of Machine Learning Models	Baharan Mirzasoleiman, Jeff Bilmes, Jure Leskovec	Link	Link
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning	Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford	Link	Link
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules	Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio	Link	None
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach	Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard Zemel, Craig Boutilier	Link	Link
Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time	Zahra Monfared, Daniel Durstewitz	Link	Link
Efficiently Learning Adversarially Robust Halfspaces with Noise	Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro	Link	None
An end-to-end approach for the verification problem: learning the right distance	Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm, Tiago Falk	Link	Link
Confidence-Aware Learning for Deep Neural Networks	Jooyoung Moon, Jihyo Kim, Younghak Shin, Sangheum Hwang	Link	Link
Topological Autoencoders	Michael Moor, Max Horn, Bastian Rieck, Karsten Borgwardt	Link	Link
Explainable k-Means and k-Medians Clustering	Michal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian, Nave Frost	Link	Link
Fair Learning with Private Demographic Data	Hussein Mozannar, Mesrob Ohannessian, Nathan Srebro	Link	Link
Consistent Estimators for Learning to Defer to an Expert	Hussein Mozannar, David Sontag	Link	Link
Continuous-time Lower Bounds for Gradient-based Algorithms	Michael Muehlebach, Michael Jordan	Link	Link
Two Simple Ways to Learn Individual Fairness Metrics from Data	Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun	Link	Link
Unique Properties of Flat Minima in Deep Networks	Rotem Mulayoff, Tomer Michaeli	Link	Link
Fast computation of Nash Equilibria in Imperfect Information Games	Remi Munos, Julien Perolat, Jean-Baptiste Lespiau, Mark Rowland, Bart De Vylder, Marc Lanctot, Finbarr Timbers, Daniel Hennes, Shayegan Omidshafiei, Audrunas Gruslys, Mohammad Gheshlaghi Azar, Edward Lockhart, Karl Tuyls	Link	Link
Missing Data Imputation using Optimal Transport	Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi	Link	Link
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees	Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar	Link	Link
Full Law Identification in Graphical Models of Missing Data: Completeness Results	Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser	Link	Link
Voice Separation with an Unknown Number of Multiple Speakers	Eliya Nachmani, Yossi Adi, Lior Wolf	Link	None
Reliable Fidelity and Diversity Metrics for Generative Models	Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh, Yunjey Choi, Jaejun Yoo	Link	Link
From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics	Sai Ganesh Nagarajan, David Balduzzi, Georgios Piliouras	Link	Link
Up or Down? Adaptive Rounding for Post-Training Quantization	Markus Nagel, Rana Ali Amjad, Mart Van Baalen, Christos Louizos, Tijmen Blankevoort	Link	Link
Goal-Aware Prediction: Learning to Model What Matters	Suraj Nair, Silvio Savarese, Chelsea Finn	Link	Link
PolyGen: An Autoregressive Generative Model of 3D Meshes	Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter Battaglia	Link	Link
Bayesian Sparsification of Deep C-valued Networks	Ivan Nazarov, Evgeny Burnaev	Link	Link
Oracle Efficient Private Non-Convex Optimization	Seth Neel, Aaron Roth, Giuseppe Vietri, Steven Wu	Link	Link
Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization	Geoffrey Negiar, Gideon Dresdner, Alicia Tsai, Laurent El Ghaoui, Francesco Locatello, Robert Freund, Fabian Pedregosa	Link	Link
In Defense of Uniform Convergence: Generalization via Derandomization with an Application to Interpolating Predictors	Jeffrey Negrea, Gintare Karolina Dziugaite, Daniel Roy	Link	Link
Involutive MCMC: a Unifying Framework	Kirill Neklyudov, Max Welling, Evgenii Egorov, Dmitry Vetrov	Link	Link
Aggregation of Multiple Knockoffs	Tuan-Binh Nguyen, Jerome-Alexis Chevalier, Bertrand Thirion, Sylvain Arlot	Link	Link
LEEP: A New Measure to Evaluate Transferability of Learned Representations	Cuong Nguyen, Tal Hassner, Matthias Seeger, Cedric Archambeau	Link	Link
Graph Homomorphism Convolution	Hoang Nguyen, Takanori Maehara	Link	Link
Knowing The What But Not The Where in Bayesian Optimization	Vu Nguyen, Michael A. Osborne	Link	Link
Robust Bayesian Classification Using An Optimistic Score Ratio	Viet Anh Nguyen, Nian Si, Jose Blanchet	Link	Link
Streaming k-Submodular Maximization under Noise subject to Size Constraint	Lan Nguyen, My T. Thai	Link	Link
LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction	Vlad Niculae, Andre Martins	Link	Link
Semi-Supervised StyleGAN for Disentanglement Learning	Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit Patel, Animashree Anandkumar	Link	Link
Supervised learning: no loss no cry	Richard Nock, Aditya Menon	Link	Link
Consistent Structured Prediction with Max-Min Margin Markov Networks	Alex Nowak, Francis Bach, Alessandro Rudi	Link	Link
T-Basis: a Compact Representation for Neural Networks	Anton Obukhov, Maxim Rakhuba, Stamatios Georgoulis, Menelaos Kanakis, Dengxin Dai, Luc Van Gool	Link	None
Eliminating the Invariance on the Loss Landscape of Linear Autoencoders	Reza Oftadeh, Jiayi Shen, Zhangyang Wang, Dylan Shell	Link	Link
On the (In)tractability of Computing Normalizing Constants for the Product of Determinantal Point Processes	Naoto Ohsaka, Tatsuya Matsuoka	Link	Link
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?	Kei Ota, Tomoaki Oiki, Devesh Jha, Toshisada Mariyama, Daniel Nikovski	Link	Link
Interferometric Graph Transform: a Deep Unsupervised Graph Representation	Edouard Oyallon	Link	Link
Learning to Score Behaviors for Guided Policy Optimization	Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Krzysztof Choromanski, Anna Choromanska, Michael Jordan	Link	[Link](https://github.com/ behaviorguidedRL/BGRL)
Neural Clustering Processes	Ari Pakman, Yueqi Wang, Catalin Mitelut, Jinhyung Lee, Liam Paninski	Link	Link
Recovery of Sparse Signals from a Mixture of Linear Samples	Soumyabrata Pal, Arya Mazumdar	Link	Link
Adversarial Mutual Information for Text Generation	Boyuan Pan, Yazheng Yang, Kaizhao Liang, Bhavya Kailkhura, Zhongming Jin, Xian-Sheng Hua, Deng Cai, Bo Li	Link	Link
Stabilizing Transformers for Reinforcement Learning	Emilio Parisotto, Francis Song, Jack Rae, Razvan Pascanu, Caglar Gulcehre, Siddhant Jayakumar, Max Jaderberg, Raphaël Lopez Kaufman, Aidan Clark, Seb Noury, Matthew Botvinick, Nicolas Heess, Raia Hadsell	Link	Link
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis	Jung Yeon Park, Kenneth Carr, Stephan Zheng, Yisong Yue, Rose Yu	Link	Link
Meta Variance Transfer: Learning to Augment from the Others	Seong-Jin Park, Seungju Han, Ji-Won Baek, Insoo Kim, Juhwan Song, Hae Beom Lee, Jae-Joon Han, Sung Ju Hwang	Link	Link
Structured Policy Iteration for Linear Quadratic Regulator	Youngsuk Park, Ryan Rossi, Zheng Wen, Gang Wu, Handong Zhao	Link	Link
Regularized Optimal Transport is Ground Cost Adversarial	François-Pierre Paty, Marco Cuturi	Link	Link
Reducing Sampling Error in Batch Temporal Difference Learning	Brahma Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone	Link	Link
Acceleration through spectral density estimation	Fabian Pedregosa, Damien Scieur	Link	Link
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits	Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van Den Broeck, Kristian Kersting, Zoubin Ghahramani	Link	Link
Learning Selection Strategies in Buchberger’s Algorithm	Dylan Peifer, Michael Stillman, Daniel Halpern-Leistner	Link	Link
Non-Autoregressive Neural Text-to-Speech	Kainan Peng, Wei Ping, Zhao Song, Kexin Zhao	Link	None
Performative Prediction	Juan Perdomo, Tijana Zrnic, Celestine Mendler-Dünner, Moritz Hardt	Link	Link
Constructive Universal High-Dimensional Distribution Generation through Deep ReLU Networks	Dmytro Perekrestenko, Stephan Müller, Helmut Bölcskei	Link	None
Budgeted Online Influence Maximization	Pierre Perrault, Jennifer Healey, Zheng Wen, Michal Valko	Link	Link
Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks	Adeel Pervez, Taco Cohen, Efstratios Gavves	Link	Link
On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent	Scott Pesme, Aymeric Dieuleveut, Nicolas Flammarion	Link	Link
Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning	Aleksei Petrenko, Zhehui Huang, Tushar Kumar, Gaurav Sukhatme, Vladlen Koltun	Link	Link
IPBoost – Non-Convex Boosting via Integer Programming	Marc Pfetsch, Sebastian Pokutta	Link	Link
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm	Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui	Link	Link
Scalable Differential Privacy with Certified Robustness in Adversarial Learning	Hai Phan, My T. Thai, Han Hu, Ruoming Jin, Tong Sun, Dejing Dou	Link	Link
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks	Mert Pilanci, Tolga Ergen	Link	Link
WaveFlow: A Compact Flow-based Model for Raw Audio	Wei Ping, Kainan Peng, Kexin Zhao, Zhao Song	Link	Link
Randomization matters How to defend against strong adversarial attacks	Rafael Pinot, Raphael Ettedgui, Geovani Rizk, Yann Chevaleyre, Jamal Atif	Link	Link
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition	Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi	Link	Link
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation	Konstantinos Pitas	Link	Link
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning	Silviu Pitis, Harris Chan, Stephen Zhao, Bradly Stadie, Jimmy Ba	Link	Link
Explaining Groups of Points in Low-Dimensional Representations	Gregory Plumb, Jonathan Terhorst, Sriram Sankararaman, Ameet Talwalkar	Link	Link
On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness	Sebastian Pokutta, Mohit Singh, Alfredo Torrico	Link	Link
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning	Vitchyr Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, Sergey Levine	Link	Link
SoftSort: A Continuous Relaxation for the argsort Operator	Sebastian Prillo, Julian Eisenschlos	Link	Link
Graph-based Nearest Neighbor Search: From Practice to Theory	Liudmila Prokhorenkova, Aleksandr Shekhovtsov	Link	Link
Adversarial Risk via Optimal Transport and Optimal Couplings	Muni Sreenivas Pydi, Varun Jog	Link	Link
Deep Isometric Learning for Visual Recognition	Haozhi Qi, Chong You, Xiaolong Wang, Yi Ma, Jitendra Malik	Link	Link
Unsupervised Speech Decomposition via Triple Information Bottleneck	Kaizhi Qian, Yang Zhang, Shiyu Chang, Mark Hasegawa-Johnson, David Cox	Link	Link
Scalable Differentiable Physics for Learning and Control	Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin	Link	Link
Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis	Shuang Qiu, Xiaohan Wei, Zhuoran Yang	Link	Link
Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs	Meng Qu, Tianyu Gao, Louis-Pascal Xhonneux, Jian Tang	Link	Link
DeepCoDA: personalized interpretability for compositional health data	Thomas Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh	Link	Link
Fast and Private Submodular and $k$-Submodular Functions Maximization with Matroid Constraints	Akbar Rafiey, Yuichi Yoshida	Link	Link
Transparency Promotion with Model-Agnostic Linear Competitors	Hassan Rafique, Tong Wang, Qihang Lin, Arshia Singhani	Link	Link
Understanding and Mitigating the Tradeoff between Robustness and Accuracy	Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John Duchi, Percy Liang	Link	Link
Fast Adaptation to New Environments via Policy-Dynamics Value Functions	Roberta Raileanu, Max Goldstein, Arthur Szlam, Rob Fergus	Link	Link
Improving Robustness of Deep-Learning-Based Image Reconstruction	Ankit Raj, Yoram Bresler, Bo Li	Link	Link
Multi-Precision Policy Enforced Training (MuPPET) : A Precision-Switching Strategy for Quantised Fixed-Point Training of CNNs	Aditya Rajagopal, Diederik Vink, Stylianos Venieris, Christos-Savvas Bouganis	Link	Link
A Game Theoretic Framework for Model Based Reinforcement Learning	Aravind Rajeswaran, Igor Mordatch, Vikash Kumar	Link	Link
Closing the convergence gap of SGD without replacement	Shashank Rajput, Anant Gupta, Dimitris Papailiopoulos	Link	Link
Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning	Amin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu, Adish Singla	Link	Link
Implicit Generative Modeling for Efficient Exploration	Neale Ratzlaff, Qinxun Bai, Li Fuxin, Wei Xu	Link	Link
Universal Equivariant Multilayer Perceptrons	Siamak Ravanbakhsh	Link	None
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch	Esteban Real, Chen Liang, David So, Quoc Le	Link	Link
Learning Human Objectives by Evaluating Hypothetical Behavior	Siddharth Reddy, Anca Dragan, Sergey Levine, Shane Legg, Jan Leike	Link	Link
Optimistic Bounds for Multi-output Learning	Henry Reeve, Ata Kaban	Link	Link
Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation	Florence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates	Link	Link
The Sample Complexity of Best-$k$ Items Selection from Pairwise Comparisons	Wenbo Ren, Jia Liu, Ness Shroff	Link	Link
NetGAN without GAN: From Random Walks to Low-Rank Approximations	Luca Rendsburg, Holger Heidrich, Ulrike Von Luxburg	Link	Link
Normalizing Flows on Tori and Spheres	Danilo Jimenez Rezende, George Papamakarios, Sebastien Racaniere, Michael Albergo, Gurtej Kanwar, Phiala Shanahan, Kyle Cranmer	Link	Link
Overfitting in adversarially robust deep learning	Leslie Rice, Eric Wong, Zico Kolter	Link	[Link](https://github.com/ locuslab/robust_overfitting)
Decentralised Learning with Random Features and Distributed Gradient Descent	Dominic Richards, Patrick Rebeschini, Lorenzo Rosasco	Link	Link
Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge	Laura Rieger, Chandan Singh, William Murdoch, Bin Yu	Link	Link
Strength from Weakness: Fast Learning Using Weak Supervision	Joshua Robinson, Stefanie Jegelka, Suvrit Sra	Link	Link
On Semi-parametric Inference for BART	Veronika Rockova	Link	Link
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training	Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh	Link	Link
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning	Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Bjorkegren, Moritz Hardt, Joshua Blumenstock	Link	Link
Double-Loop Unadjusted Langevin Algorithm	Paul Rolland, Armin Eftekhari, Ali Kavis, Volkan Cevher	Link	Link
Reverse-engineering deep ReLU networks	David Rolnick, Konrad Kording	Link	Link
Attentive Group Equivariant Convolutional Networks	David Romero, Erik Bekkers, Jakub Tomczak, Mark Hoogendoorn	Link	Link
Finite-Time Convergence in Continuous-Time Optimization	Orlando Romero, Mouhacine Benosman	Link	Link
Near-optimal Regret Bounds for Stochastic Shortest Path	Aviv Rosenberg, Alon Cohen, Yishay Mansour, Haim Kaplan	Link	Link
Predicting Choice with Set-Dependent Aggregation	Nir Rosenfeld, Kojin Oshiba, Yaron Singer	Link	Link
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing	Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar, Zico Kolter	Link	Link
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning	Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Bjorn Ommer, Joseph Paul Cohen	Link	Link
FetchSGD: Communication-Efficient Federated Learning with Sketching	Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora	Link	Link
Simple and sharp analysis of k-means			Václav Rozhoň
Bayesian Optimisation over Multiple Continuous and Categorical Inputs	Binxin Ru, Ahsan Alvi, Vu Nguyen, Michael A. Osborne, Stephen Roberts	Link	Link
Inter-domain Deep Gaussian Processes	Tim G. J. Rudner, Dino Sejdinovic, Yarin Gal	Link	Link
Bio-Inspired Hashing for Unsupervised Similarity Search	Chaitanya Ryali, John Hopfield, Leopold Grinberg, Dmitry Krotov	Link	Link
Adversarial Attacks on Copyright Detection Systems	Parsa Saadatpanah, Ali Shafahi, Tom Goldstein	Link	None
Bounding the fairness and accuracy of classifiers from population statistics	Sivan Sabato, Elad Yom-Tov	Link	Link
Radioactive data: tracing through training	Alexandre Sablayrolles, Matthijs Douze, Cordelia Schmid, Herve Jegou	Link	Link
Causal Structure Discovery from Distributions Arising from Mixtures of DAGs	Basil Saeed, Snigdha Panigrahi, Caroline Uhler	Link	Link
An Investigation of Why Overparameterization Exacerbates Spurious Correlations	Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh, Percy Liang	Link	Link
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards	Aadirupa Saha, Pierre Gaillard, Michal Valko	Link	Link
From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model	Aadirupa Saha, Aditya Gopalan	Link	Link
Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics	Debjani Saha, Candice Schumann, Duncan Mcelfresh, John Dickerson, Michelle Mazurek, Michael Tschantz	Link	Link
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models	Aytunc Sahin, Yatao Bian, Joachim Buhmann, Andreas Krause	Link	Link
Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models	Yuta Saito, Shota Yasui	Link	Link
Inferring DQN structure for high-dimensional continuous control	Andrey Sakryukin, Chedy Raissi, Mohan Kankanhalli	Link	Link
The Performance Analysis of Generalized Margin Maximizers on Separable Data	Fariborz Salehi, Ehsan Abbasi, Babak Hassibi	Link	Link
Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization	Sudeep Salgia, Qing Zhao, Sattar Vakili	Link	Link
A Quantile-based Approach for Hyperparameter Transfer Learning	David Salinas, Huibin Shen, Valerio Perrone	Link	Link
Spectral Subsampling MCMC for Stationary Time Series	Robert Salomone, Matias Quiroz, Robert Kohn, Mattias Villani, Minh-Ngoc Tran	Link	Link
Learning to Simulate Complex Physics with Graph Networks	Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying, Jure Leskovec, Peter Battaglia	Link	Link
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent	Karthik Abinav Sankararaman, Soham De, Zheng Xu, W. Ronny Huang, Tom Goldstein	Link	Link
Explicit Gradient Learning for Black-Box Optimization	Elad Sarafian, Mor Sinay, Yoram Louzoun, Noa Agmon, Sarit Kraus	Link	Link
Detecting Out-of-Distribution Examples with Gram Matrices	Chandramouli Shama Sastry, Sageev Oore	Link	Link
Constrained Markov Decision Processes via Backward Value Functions	Harsh Satija, Philip Amortila, Joelle Pineau	Link	Link
A Sample Complexity Separation between Non-Convex and Convex Meta-Learning	Nikunj Saunshi, Yi Zhang, Mikhail Khodak, Sanjeev Arora	Link	Link
Harmonic Decompositions of Convolutional Networks	Meyer Scetbon, Zaid Harchaoui	Link	None
Implicit competitive regularization in GANs	Florian Schaefer, Hongkai Zheng, Animashree Anandkumar	Link	Link
Off-Policy Actor-Critic with Shared Experience Replay	Simon Schmitt, Matteo Hessel, Karen Simonyan	Link	Link
Discriminative Adversarial Search for Abstractive Summarization	Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, Benjamin Piwowarski, Jacopo Staiano	Link	Link
Universal Asymptotic Optimality of Polyak Momentum	Damien Scieur, Fabian Pedregosa	Link	None
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures	Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain Couillet	Link	Link
Planning to Explore via Self-Supervised World Models	Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak	Link	Link
An Explicitly Relational Neural Network Architecture	Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David Barrett, Marta Garnelo	Link	Link
Optimistic Policy Optimization with Bandit Feedback	Lior Shani, Yonathan Efroni, Aviv Rosenberg, Shie Mannor	Link	None
Neural Kernels Without Tangents	Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Jonathan Ragan-Kelley, Ludwig Schmidt, Benjamin Recht	Link	Link
Learning Robot Skills with Temporal Variational Inference	Tanmay Shankar, Abhinav Gupta	Link	Link
Evaluating Machine Accuracy on ImageNet	Vaishaal Shankar, Rebecca Roelofs, Horia Mania, Alex Fang, Benjamin Recht, Ludwig Schmidt	Link	Link
Channel Equilibrium Networks for Learning Deep Representation	Wenqi Shao, Shitao Tang, Xingang Pan, Ping Tan, Xiaogang Wang, Ping Luo	Link	Link
ControlVAE: Controllable Variational Autoencoder	Huajie Shao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Dongxin Liu, Jun Wang, Tarek Abdelzaher	Link	Link
Lookahead-Bounded Q-learning	Ibrahim El Shar, Daniel Jiang	Link	Link
Causal Strategic Linear Regression	Yonadav Shavit, Benjamin Edelman, Brian Axelrod	Link	Link
Adaptive Sampling for Estimating Probability Distributions	Shubhanshu Shekhar, Tara Javidi, Mohammad Ghavamzadeh	Link	Link
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions	Zhengyang Shen, Lingshen He, Zhouchen Lin, Jinwen Ma	Link	Link
Deep Reinforcement Learning with Robust and Smooth Policy	Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao	Link	Link
Educating Text Autoencoders: Latent Representation Guidance via Denoising	Tianxiao Shen, Jonas Mueller, Dr.Regina Barzilay, Tommi Jaakkola	Link	Link
Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints	Cong Shen, Zhiyang Wang, Sofia Villar, Mihaela Van Der Schaar	Link	Link
PowerNorm: Rethinking Batch Normalization in Transformers	Sheng Shen, Zhewei Yao, Amir Gholami, Michael Mahoney, Kurt Keutzer	Link	Link
Extreme Multi-label Classification from Aggregated Labels	Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit Dhillon	Link	Link
One-shot Distributed Ridge Regression in High Dimensions	Yue Sheng, Edgar Dobriban	Link	Link
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks	Alexander Shevchenko, Marco Mondelli	Link	Link
Incremental Sampling Without Replacement for Sequence Models	Kensen Shi, David Bieber, Charles Sutton	Link	Link
Message Passing Least Squares Framework and its Application to Rotation Synchronization	Yunpeng Shi, Gilad Lerman	Link	Link
Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making	Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng	Link	Link
A Graph to Graphs Framework for Retrosynthesis Prediction	Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang	Link	None
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective	Baifeng Shi, Dinghuai Zhang, Qi Dai, Zhanxing Zhu, Yadong Mu, Jingdong Wang	Link	Link
Dispersed Exponential Family Mixture VAEs for Interpretable Text Generation	Wenxian Shi, Hao Zhou, Ning Miao, Lei Li	Link	Link
On Conditional Versus Marginal Bias in Multi-Armed Bandits	Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo	Link	Link
Predictive Coding for Locally-Linear Control	Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung Bui	Link	Link
A Markov Decision Process Model for Socio-Economic Systems Impacted by Climate Change	Salman Sadiq Shuvo, Yasin Yilmaz, Alan Bush, Mark Hafen	Link	Link
Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits	Nian Si, Fan Zhang, Zhengyuan Zhou, Jose Blanchet	Link	Link
Piecewise Linear Regression via a Difference of Convex Functions	Ali Siahkamari, Aditya Gangrade, Brian Kulis, Venkatesh Saligrama	Link	Link
Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards	Umer Siddique, Paul Weng, Matthieu Zimmer	Link	Link
Deep Gaussian Markov Random Fields	Per Sidén, Fredrik Lindsten	Link	Link
Collaborative Machine Learning with Incentive-Aware Model Rewards	Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low	Link	Link
Naive Exploration is Optimal for Online LQR	Max Simchowitz, Dylan Foster	Link	Link
A Generative Model for Molecular Distance Geometry	Gregor Simm, Jose Miguel Hernandez-Lobato	Link	Link
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics	Gregor Simm, Robert Pinsler, Jose Miguel Hernandez-Lobato	Link	Link
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise	Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gurbuzbalaban	Link	Link
Second-Order Provable Defenses against Adversarial Attacks	Sahil Singla, Soheil Feizi	Link	Link
FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis	Aman Sinha, Matthew O’Kelly, Hongrui Zheng, Rahul Mangharam, John Duchi, Russ Tedrake	Link	Link
Small-GAN: Speeding up GAN Training using Core-Sets	Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena	Link	None
Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device Failure	John Sipple	Link	Link
Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis	Vidyashankar Sivakumar, Steven Wu, Arindam Banerjee	Link	None
Optimizer Benchmarking Needs to Account for Hyperparameter Tuning	Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret	Link	Link
When Explanations Lie: Why Many Modified BP Attributions Fail	Leon Sixt, Maximilian Granz, Tim Landgraf	Link	Link
On the Generalization Benefit of Noise in Stochastic Gradient Descent	Samuel Smith, Erich Elsen, Soham De	Link	Link
Multiclass Neural Network Minimization via Tropical Newton Polytope Approximation	Georgios Smyrnis, Petros Maragos	Link	Link
Bridging the Gap Between f-GANs and Wasserstein GANs	Jiaming Song, Stefano Ermon	Link	Link
Provably Efficient Model-based Policy Adaptation	Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao	Link	Link
Hypernetwork approach to generating point clouds	Przemysław Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski	Link	Link
Robustness to Spurious Correlations via Human Annotations	Megha Srivastava, Tatsunori Hashimoto, Percy Liang	Link	Link
Which Tasks Should Be Learned Together in Multi-task Learning?	Trevor Standley, Amir Zamir, Dawn Chen, Leonidas Guibas, Jitendra Malik, Silvio Savarese	Link	Link
Responsive Safety in Reinforcement Learning by PID Lagrangian Methods	Adam Stooke, Joshua Achiam, Pieter Abbeel	Link	Link
Learning Discrete Structured Representations by Adversarially Maximizing Mutual Information	Karl Stratos, Sam Wiseman	Link	Link
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks	David Stutz, Matthias Hein, Bernt Schiele	Link	Link
Doubly robust off-policy evaluation with shrinkage	Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudik	Link	Link
Task Understanding from Confusing Multi-task Data	Xin Su, Yizhou Jiang, Shangqi Guo, Feng Chen	Link	Link
ConQUR: Mitigating Delusional Bias in Deep Q-Learning	Dijia Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier	Link	Link
Adaptive Estimator Selection for Off-Policy Evaluation	Yi Su, Pavithra Srinath, Akshay Krishnamurthy	Link	Link
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data	Felipe Petroski Such, Aditya Rawal, Joel Lehman, Kenneth Stanley, Jeffrey Clune	Link	Link
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking	Haoran Sun, Songtao Lu, Mingyi Hong	Link	Link
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts	Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei Efros, Moritz Hardt	Link	Link
An EM Approach to Non-autoregressive Conditional Sequence Generation	Zhiqing Sun, Yiming Yang	Link	Link
The Shapley Taylor Interaction Index	Mukund Sundararajan, Kedar Dhamdhere, Ashish Agarwal	Link	Link
The Many Shapley Values for Model Explanation	Mukund Sundararajan, Amir Najmi	Link	None
Multi-objective Bayesian Optimization using Pareto-frontier Entropy	Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama	Link	Link
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks	Jakub Swiatkowski, Kevin Roth, Bastiaan Veeling, Linh Tran, Joshua Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin	Link	Link
Multi-Agent Routing Value Iteration Network	Quinlan Sykora, Mengye Ren, Raquel Urtasun	Link	Link
Distinguishing Cause from Effect Using Quantiles: Bivariate Quantile Causal Discovery	Natasa Tagasovska, Valérie Chavez-Demoulin, Thibault Vatter	Link	Link
Quantized Decentralized Stochastic Learning over Directed Graphs	Hossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani	Link	Link
Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization	Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama	Link	Link
Fiedler Regularization: Learning Neural Networks with Graph Sparsity	Edric Tam, David Dunson	Link	Link
DropNet: Reducing Neural Network Complexity via Iterative Pruning	Chong Min John Tan, Mehul Motani	Link	Link
Reinforcement Learning for Integer Programming: Learning to Cut	Yunhao Tang, Shipra Agrawal, Yuri Faenza	Link	Link
The Buckley-Osthus model and the block preferential attachment model: statistical analysis and application	Wenpin Tang, Xin Guo, Fengmin Tang	Link	Link
Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies	Shengpu Tang, Aditya Modi, Michael Sjoding, Jenna Wiens	Link	Link
Taylor Expansion Policy Optimization	Yunhao Tang, Michal Valko, Remi Munos	Link	Link
Variational Imitation Learning with Diverse-quality Demonstrations	Voot Tangkaratt, Bo Han, Mohammad Emtiyaz Khan, Masashi Sugiyama	Link	Link
Learning disconnected manifolds: a no GAN’s land	Ugo Tanielian, Thibaut Issenhuth, Elvis Dohmatob, Jeremie Mary	Link	Link
No-Regret Exploration in Goal-Oriented Reinforcement Learning	Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric	Link	Link
Sparse Sinkhorn Attention	Yi Tay, Dara Bahri, Liu Yang, Donald Metzler, Da-Cheng Juan	Link	None
Inductive Relation Prediction by Subgraph Reasoning	Komal Teru, Etienne Denis, Will Hamilton	Link	Link
Few-shot Domain Adaptation by Causal Mechanism Transfer	Takeshi Teshima, Issei Sato, Masashi Sugiyama	Link	Link
Student Specialization in Deep Rectified Networks With Finite Width and Input Dimension	Yuandong Tian	Link	Link
Sequential Transfer in Reinforcement Learning with a Generative Model	Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli	Link	Link
Convolutional dictionary learning based auto-encoders for natural exponential-family distributions	Bahareh Tolooshams, Andrew Song, Simona Temereanca, Demba Ba	Link	Link
Multi-step Greedy Reinforcement Learning Algorithms	Manan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh	Link	Link
Choice Set Optimization Under Discrete Choice Models of Group Decisions	Kiran Tomlinson, Austin Benson	Link	Link
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics	Alexander Tong, Jessie Huang, Guy Wolf, David Van Dijk, Smita Krishnaswamy	Link	Link
Alleviating Privacy Attacks via Causal Learning	Shruti Tople, Amit Sharma, Aditya Nori	Link	Link
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	Csaba Toth, Harald Oberhauser	Link	Link
Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations	Florian Tramer, Jens Behrmann, Nicholas Carlini, Nicolas Papernot, Joern-Henrik Jacobsen	Link	Link
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization	Quoc Tran-Dinh, Nhan Pham, Lam Nguyen	Link	Link
Bayesian Differential Privacy for Machine Learning	Aleksei Triastcyn, Boi Faltings	Link	Link
Single Point Transductive Prediction	Nilesh Tripuraneni, Lester Mackey	Link	Link
GraphOpt: Learning Optimization Models of Graph Formation	Rakshit Trivedi, Jiachen Yang, Hongyuan Zha	Link	Link
Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources	Yun-Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho	Link	Link
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks	Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry	Link	Link
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis	Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama	Link	Link
Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network	Javier Turek, Shailee Jain, Vy Vo, Mihai Capotă, Alexander Huth, Theodore Willke	Link	Link
Minimax Weight and Q-Function Learning for Off-Policy Evaluation	Masatoshi Uehara, Jiawei Huang, Nan Jiang	Link	Link
StochasticRank: Global Optimization of Scale-Free Discrete Functions	Aleksei Ustimenko, Liudmila Prokhorenkova	Link	Link
Undirected Graphical Models as Approximate Posteriors	Arash Vahdat, Evgeny Andriyash, William Macready	Link	Link
Uncertainty Estimation Using a Single Deep Deterministic Neural Network	Joost Van Amersfoort, Lewis Smith, Yee Whye Teh, Yarin Gal	Link	Link
Deep Molecular Programming: A Natural Implementation of Binary-Weight ReLU Neural Networks	Marko Vasic, Cameron Chalk, Sarfraz Khurshid, David Soloveichik	Link	None
Linear bandits with Stochastic Delayed Feedback	Claire Vernade, Alexandra Carpentier, Tor Lattimore, Giovanni Zappella, Beyza Ermis, Michael Brückner	Link	Link
Non-Stationary Delayed Bandits with Intermediate Observations	Claire Vernade, Andras Gyorgy, Timothy Mann	Link	Link
OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning	Alexander Vezhnevets, Yuhuai Wu, Maria Eckstein, Rémi Leblond, Joel Z Leibo	Link	None
Born-Again Tree Ensembles	Thibaut Vidal, Maximilian Schiffer	Link	Link
Private Reinforcement Learning with PAC and Regret Guarantees	Giuseppe Vietri, Borja Balle, Akshay Krishnamurthy, Steven Wu	Link	Link
New Oracle-Efficient Algorithms for Private Synthetic Data Release	Giuseppe Vietri, Grace Tian, Mark Bun, Thomas Steinke, Steven Wu	Link	Link
Conditional gradient methods for stochastically constrained convex minimization	Maria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher	Link	Link
Unsupervised Discovery of Interpretable Directions in the GAN Latent Space	Andrey Voynov, Artem Babenko	Link	Link
Safe Reinforcement Learning in Constrained Markov Decision Processes	Akifumi Wachi, Yanan Sui	Link	Link
Orthogonalized SGD and Nested Architectures for Anytime Neural Networks	Chengcheng Wan, Henry Hoffmann, Shan Lu, Michael Maire	Link	None
Projection-free Distributed Online Convex Optimization with $O(\sqrtT)$ Communication Complexity	Yuanyu Wan, Wei-Wei Tu, Lijun Zhang	Link	Link
Logistic Regression for Massive Data with Rare Events	Haiying Wang	Link	Link
On the Global Optimality of Model-Agnostic Meta-Learning	Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang	Link	Link
Towards Accurate Post-training Network Quantization via Bit-Split and Stitching	Peisong Wang, Qiang Chen, Xiangyu He, Jian Cheng	Link	Link
Self-Modulating Nonparametric Event-Tensor Factorization	Zheng Wang, Xinqi Chu, Shandian Zhe	Link	Link
Upper bounds for Model-Free Row-Sparse Principal Component Analysis	Guanyi Wang, Santanu Dey	Link	Link
ROMA: Multi-Agent Reinforcement Learning with Emergent Roles	Tonghan Wang, Heng Dong, Victor Lesser, Chongjie Zhang	Link	Link
Non-separable Non-stationary random fields	Kangrui Wang, Oliver Hamelijnck, Theodoros Damoulas, Mark Steel	Link	Link
Continuously Indexed Domain Adaptation	Hao Wang, Hao He, Dina Katabi	Link	Link
Learning Efficient Multi-agent Communication: An Information Bottleneck Approach	Rundong Wang, Xu He, Runsheng Yu, Wei Qiu, Bo An, Zinovi Rabinovich	Link	Link
Frustratingly Simple Few-Shot Object Detection	Xin Wang, Thomas Huang, Joseph Gonzalez, Trevor Darrell, Fisher Yu	Link	Link
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere	Tongzhou Wang, Phillip Isola	Link	Link
Enhanced POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions	Rui Wang, Joel Lehman, Aditya Rawal, Jiale Zhi, Yulun Li, Jeffrey Clune, Kenneth Stanley	Link	Link
Haar Graph Pooling	Yu Guang Wang, Ming Li, Zheng Ma, Guido Montufar, Xiaosheng Zhuang, Yanan Fan	Link	Link
Deep Streaming Label Learning	Zhen Wang, Liu Liu, Dacheng Tao	Link	Link
BoXHED: Boosted eXact Hazard Estimator with Dynamic covariates	Xiaochen Wang, Arash Pakbin, Bobak Mortazavi, Hongyu Zhao, Donald Lee	Link	Link
Optimizing Data Usage via Differentiable Rewards	Xinyi Wang, Hieu Pham, Paul Michel, Antonios Anastasopoulos, Jaime Carbonell, Graham Neubig	Link	None
Bandits for BMO Functions	Tianyu Wang, Cynthia Rudin	Link	Link
When deep denoising meets iterative phase retrieval	Yaotian Wang, Xiaohang Sun, Jason Fleischer	Link	Link
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables	Qi Wang, Herke Van Hoof	Link	Link
Loss Function Search for Face Recognition	Xiaobo Wang, Shuo Wang, Cheng Chi, Shifeng Zhang, Tao Mei	Link	Link
Sequential Cooperative Bayesian Inference	Junqi Wang, Pei Wang, Patrick Shafto	Link	Link
Neural Network Control Policy Verification With Persistent Adversarial Perturbation	Yuh-Shyang Wang, Lily Weng, Luca Daniel	Link	Link
Cost-effectively Identifying Causal Effects When Only Response Variable is Observable	Tian-Zuo Wang, Xi-Zhu Wu, Sheng-Jun Huang, Zhi-Hua Zhou	Link	Link
Striving for Simplicity and Performance in Off-Policy DRL: Output Normalization and Non-Uniform Sampling	Che Wang, Yanqiu Wu, Quan Vuong, Keith Ross	Link	Link
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data	Di Wang, Hanshen Xiao, Srinivas Devadas, Jinhui Xu	Link	Link
Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning	Lingxiao Wang, Zhuoran Yang, Zhaoran Wang	Link	Link
On Lp-norm Robustness of Ensemble Decision Stumps and Trees	Yihan Wang, Huan Zhang, Hongge Chen, Duane Boning, Cho-Jui Hsieh	Link	[Link](https://github.com/YihanWang617/On-ell_p-Robustness- of-Ensemble-Stumps-and-Trees)
Thompson Sampling via Local Uncertainty	Zhendong Wang, Mingyuan Zhou	Link	Link
A Nearly-Linear Time Algorithm for Exact Community Recovery in Stochastic Block Model	Peng Wang, Zirui Zhou, Anthony Man-Cho So	Link	Link
Learning Representations that Support Extrapolation	Taylor Webb, Zachary Dulberg, Steven Frankland, Alexander Petrov, Randall O’Reilly, Jonathan Cohen	Link	Link
PoKED: A Semi-Supervised System for Word Sense Disambiguation	Feng Wei	Link	None
Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems	Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schönlieb, Hua Huang	Link	Link
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes	Chen-Yu Wei, Mehdi Jafarnia Jahromi, Haipeng Luo, Hiteshi Sharma, Rahul Jain	Link	Link
The Implicit and Explicit Regularization Effects of Dropout	Colin Wei, Sham Kakade, Tengyu Ma	Link	Link
Online Control of the False Coverage Rate and False Sign Rate	Asaf Weinstein, Aaditya Ramdas	Link	Link
Batch Stationary Distribution Estimation	Junfeng Wen, Bo Dai, Lihong Li, Dale Schuurmans	Link	Link
Domain Aggregation Networks for Multi-Source Domain Adaptation	Junfeng Wen, Russell Greiner, Dale Schuurmans	Link	Link
Towards Understanding the Regularization of Adversarial Robustness on Neural Networks	Yuxin Wen, Shuai Li, Kui Jia	Link	Link
Amortised Learning by Wake-Sleep	Li Wenliang, Theodore Moskovitz, Heishiro Kanagawa, Maneesh Sahani	Link	Link
How Good is the Bayes Posterior in Deep Neural Networks Really?	Florian Wenzel, Kevin Roth, Bastiaan Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin	Link	Link
Predictive Sampling with Forecasting Autoregressive Models	Auke Wiggers, Emiel Hoogeboom	Link	Link
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes	William Wilkinson, Paul Chang, Michael Andersen, Arno Solin	Link	Link
Efficient nonparametric statistical inference on population feature importance using Shapley values	Brian Williamson, Jean Feng	Link	Link
Efficiently sampling functions from Gaussian process posteriors	James Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Deisenroth	Link	Link
Learning to Rank Learning Curves	Martin Wistuba, Tejaswini Pedapati	Link	Link
Causal Inference using Gaussian Processes with Structured Latent Confounders	Sam Witty, Kenta Takatsu, David Jensen, Vikash Mansinghka	Link	Link
Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling	David Woodruff, Amir Zandieh	Link	Link
Is Local SGD Better than Minibatch SGD?	Blake Woodworth, Kumar Kshitij Patel, Sebastian Stich, Zhen Dai, Brian Bullins, Brendan Mcmahan, Ohad Shamir, Nathan Srebro	Link	Link
Obtaining Adjustable Regularization for Free via Iterate Averaging	Jingfeng Wu, Vladimir Braverman, Lin Yang	Link	Link
DeltaGrad: Rapid retraining of machine learning models	Yinjun Wu, Edgar Dobriban, Susan Davidson	Link	Link
On the Noisy Gradient Descent that Generalizes as SGD	Jingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Vladimir Braverman, Zhanxing Zhu	Link	Link
Stronger and Faster Wasserstein Adversarial Attacks	Kaiwen Wu, Allen Wang, Yaoliang Yu	Link	Link
Sequence Generation with Mixed Representations	Lijun Wu, Shufang Xie, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin, Tieyan Liu	Link	Link
Adversarial Robustness via Runtime Masking and Cleansing	Yi-Hsuan Wu, Chia-Hung Yuan, Shan-Hung Wu	Link	Link
On the Generalization Effects of Linear Transformations in Data Augmentation	Sen Wu, Hongyang Zhang, Gregory Valiant, Christopher Re	Link	Link
Amortized Population Gibbs Samplers with Neural Sufficient Statistics	Hao Wu, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem Van De Meent	Link	Link
Continuous Graph Neural Networks	Louis-Pascal Xhonneux, Meng Qu, Jian Tang	Link	Link
A Flexible Framework for Nonparametric Graphical Modeling that Accommodates Machine Learning	Yunhua Xiang, Noah Simon	Link	Link
Generative Flows with Matrix Exponential	Changyi Xiao, Ligang Liu	Link	Link
Disentangling Trainability and Generalization in Deep Neural Networks	Lechao Xiao, Jeffrey Pennington, Samuel Schoenholz	Link	Link
Optimally Solving Two-Agent Decentralized POMDPs Under One-Sided Information Sharing	Yuxuan Xie, Jilles Dibangoye, Olivier Buffet	Link	Link
Maximum-and-Concatenation Networks	Xingyu Xie, Hao Kong, Jianlong Wu, Wayne Zhang, Guangcan Liu, Zhouchen Lin	Link	Link
Zeno++: Robust Fully Asynchronous SGD	Cong Xie, Sanmi Koyejo, Indranil Gupta	Link	Link
Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems	Guangzeng Xie, Luo Luo, Yijiang Lian, Zhihua Zhang	Link	Link
On the Number of Linear Regions of Convolutional Neural Networks	Huan Xiong, Lei Huang, Mengyang Yu, Li Liu, Fan Zhu, Ling Shao	Link	Link
On Layer Normalization in the Transformer Architecture	Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tieyan Liu	Link	Link
On Variational Learning of Controllable Representations for Text without Supervision	Peng Xu, Jackie Chi Kit Cheung, Yanshuai Cao	Link	Link
Class-Weighted Classification: Trade-offs and Robust Approaches	Ziyu Xu, Chen Dan, Justin Khim, Pradeep Ravikumar	Link	Link
A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation	Pan Xu, Quanquan Gu	Link	Link
Understanding and Stabilizing GANs’ Training Dynamics Using Control Theory	Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang	Link	Link
Learning Autoencoders with Relational Regularization	Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin	Link	Link
Learning Factorized Weight Matrix for Joint Filtering	Xiangyu Xu, Yongrui Ma, Wenxiu Sun	Link	None
Variational Label Enhancement	Ning Xu, Jun Shu, Yun-Peng Liu, Xin Geng	Link	None
Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control	Jie Xu, Yunsheng Tian, Pingchuan Ma, Daniela Rus, Shinjiro Sueda, Wojciech Matusik	Link	Link
MetaFun: Meta-Learning with Iterative Functional Updates	Jin Xu, Jean-Francois Ton, Hyunjik Kim, Adam Kosiorek, Yee Whye Teh	Link	Link
Video Prediction via Example Guidance	Jingwei Xu, Huazhe Xu, Bingbing Ni, Xiaokang Yang, Trevor Darrell	Link	Link
Amortized Finite Element Analysis for Fast PDE-Constrained Optimization	Tianju Xue, Alex Beatson, Sigrid Adriaenssens, Ryan Adams	Link	Link
Feature Selection using Stochastic Gates	Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger	Link	Link
Stochastic Optimization for Non-convex Inf-Projection Problems	Yan Yan, Yi Xu, Lijun Zhang, Wang Xiaoyu, Tianbao Yang	Link	Link
Variational Bayesian Quantization	Yibo Yang, Robert Bamler, Stephan Mandt	Link	Link
Energy-Based Processes for Exchangeable Data	Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans	Link	Link
Randomized Smoothing of All Shapes and Sizes	Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya Razenshteyn, Jerry Li	Link	Link
Q-value Path Decomposition for Deep Multiagent Reinforcement Learning	Yaodong Yang, Jianye Hao, Guangyong Chen, Hongyao Tang, Yingfeng Chen, Yujing Hu, Changjie Fan, Zhongyu Wei	Link	Link
Improving Molecular Design by Stochastic Iterative Target Augmentation	Kevin Yang, Wengong Jin, Kyle Swanson, Dr.Regina Barzilay, Tommi Jaakkola	Link	Link
On the consistency of top-k surrogate losses	Forest Yang, Sanmi Koyejo	Link	Link
Interpolation between Residual and Non-Residual Networks	Zonghan Yang, Yang Liu, Chenglong Bao, Zuoqiang Shi	Link	Link
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound	Lin Yang, Mengdi Wang	Link	None
Multi-Agent Determinantal Q-Learning	Yaodong Yang, Ying Wen, Jun Wang, Liheng Chen, Kun Shao, David Mguni, Weinan Zhang	Link	Link
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks	Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma	Link	Link
Unsupervised Transfer Learning for Spatiotemporal Predictive Networks	Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang	Link	Link
Searching to Exploit Memorization Effect in Learning with Noisy Labels	Quanming Yao, Hansi Yang, Bo Han, Gang Niu, James Tin-Yau Kwok	Link	Link
Graph-based, Self-Supervised Program Repair from Diagnostic Feedback	Michihiro Yasunaga, Percy Liang	Link	Link
Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Clusters for Extreme Multi-label Text Classification	Hui Ye, Zhiyu Chen, Da-Han Wang, Brian Davison	Link	Link
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection	Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam Klivans, Qiang Liu	Link	Link
It’s Not What Machines Can Learn, It’s What We Cannot Teach	Gal Yehuda, Moshe Gabel, Assaf Schuster	Link	Link
Data Valuation using Reinforcement Learning	Jinsung Yoon, Sercan Arik, Tomas Pfister	Link	Link
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning	Sung Whan Yoon, Do-Yeon Kim, Jun Seo, Jaekyun Moon	Link	Link
Robustifying Sequential Neural Processes	Jaesik Yoon, Gautam Singh, Sungjin Ahn	Link	Link
When Does Self-Supervision Help Graph Convolutional Networks?	Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen	Link	Link
Graph Structure of Neural Networks	Jiaxuan You, Jure Leskovec, Kaiming He, Saining Xie	Link	Link
Simultaneous Inference for Massive Data: Distributed Bootstrap	Yang Yu, Shih-Kang Chao, Guang Cheng	Link	Link
Graphical Models Meet Bandits: A Variational Thompson Sampling Approach	Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel	Link	Link
Label-Noise Robust Domain Adaptation	Xiyu Yu, Tongliang Liu, Mingming Gong, Kun Zhang, Kayhan Batmanghelich, Dacheng Tao	Link	Link
Intrinsic Reward Driven Imitation Learning via Generative Model	Xingrui Yu, Yueming Lyu, Ivor Tsang	Link	Link
Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters	Wenhui Yu, Zheng Qin	Link	Link
Federated Learning with Only Positive Labels	Felix Yu, Ankit Singh Rawat, Aditya Menon, Sanjiv Kumar	Link	None
Training Deep Energy-Based Models with f-Divergence Minimization	Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon	Link	Link
Graph Random Neural Features for Distance-Preserving Graph Representations	Daniele Zambon, Cesare Alippi, Lorenzo Livi	Link	Link
Learning Near Optimal Policies with Low Inherent Bellman Error	Andrea Zanette, Alessandro Lazaric, Mykel Kochenderfer, Emma Brunskill	Link	Link
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing	Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van Den Broeck	Link	Link
Learning Calibratable Policies using Programmatic Style-Consistency	Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht	Link	Link
Designing Optimal Dynamic Treatment Regimes: A Causal Reinforcement Learning Approach	Junzhe Zhang	Link	None
Robustness to Programmable String Transformations via Augmented Abstract Training	Yuhao Zhang, Aws Albarghouthi, Loris D’Antoni	Link	Link
Converging to Team-Maxmin Equilibria in Zero-Sum Multiplayer Games	Youzhi Zhang, Bo An	Link	Link
Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate	Yufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang	Link	Link
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings	Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman	Link	Link
Learning the Valuations of a $k$-demand Agent	Hanrui Zhang, Vincent Conitzer	Link	Link
A Tree-Structured Decoder for Image-to-Markup Generation	Jianshu Zhang, Jun Du, Yongxin Yang, Yi-Zhe Song, Si Wei, Lirong Dai	Link	Link
Approximation Capabilities of Neural ODEs and Invertible Residual Networks	Han Zhang, Xi Gao, Jacob Unterman, Tom Arodz	Link	None
Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization	Richard Zhang, Daniel Golovin	Link	Link
Spread Divergence	Mingtian Zhang, Peter Hayes, Thomas Bird, Raza Habib, David Barber	Link	Link
Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning	Jize Zhang, Bhavya Kailkhura, T. Yong-Jin Han	Link	Link
Privately Learning Markov Random Fields	Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni, Steven Wu	Link	Link
Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective	Ruixiang Zhang, Masanori Koyama, Katsuhiko Ishiguro	Link	Link
Optimal Estimator for Unlabeled Linear Regression	Hang Zhang, Ping Li	Link	Link
Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks	Yonggang Zhang, Ya Li, Tongliang Liu, Xinmei Tian	Link	Link
Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions	Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka, Suvrit Sra, Ali Jadbabaie	Link	Link
Self-Attentive Hawkes Process	Qiang Zhang, Aldo Lipani, Omer Kirnap, Emine Yilmaz	Link	Link
GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values	Shangtong Zhang, Bo Liu, Shimon Whiteson	Link	Link
Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation	Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson	Link	Link
Invariant Causal Prediction for Block MDPs	Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup	Link	Link
Adaptive Reward-Poisoning Attacks against Reinforcement Learning	Xuezhou Zhang, Yuzhe Ma, Adish Singla, Xiaojin Zhu	Link	Link
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods	Wei Zhang, Thomas Panum, Somesh Jha, Prasad Chalasani, David Page	Link	Link
Convex Calibrated Surrogates for the Multi-Label F-Measure	Mingyuan Zhang, Harish Guruprasad Ramaswamy, Shivani Agarwal	Link	Link
Sparsified Linear Programming for Zero-Sum Equilibrium Finding	Brian Zhang, Tuomas Sandholm	Link	Link
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case	Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong	Link	Link
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger	Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan Kankanhalli	Link	Link
A Flexible Latent Space Model for Multilayer Networks	Xuefei Zhang, Songkai Xue, Ji Zhu	Link	Link
Perceptual Generative Autoencoders	Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull	Link	Link
Variance Reduction in Stochastic Particle-Optimization Sampling	Jianyi Zhang, Yang Zhao, Changyou Chen	Link	Link
Learning with Feature and Distribution Evolvable Streams	Zhen-Yu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou	Link	Link
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization	Jingqing Zhang, Yao Zhao, Mohammad Saleh, Peter Liu	Link	Link
On Leveraging Pretrained GANs for Generation with Limited Data	Miaoyun Zhao, Yulai Cong, Lawrence Carin	Link	Link
On Learning Language-Invariant Representations for Universal Machine Translation	Han Zhao, Junjie Hu, Andrej Risteski	Link	Link
Do RNN and LSTM have Long Memory?	Jingyu Zhao, Feiqing Huang, Jia Lv, Yanjie Duan, Zhen Qin, Guodong Li, Guangjian Tian	Link	Link
Feature Quantization Improves GAN Training	Yang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen	Link	Link
Individual Calibration with Randomized Forecasting	Shengjia Zhao, Tengyu Ma, Stefano Ermon	Link	Link
Smaller, more accurate regression forests using tree alternating optimization	Arman Zharmagambetov, Miguel Carreira-Perpinan	Link	Link
Learning to Learn Kernels with Variational Random Features	Xiantong Zhen, Haoliang Sun, Yingjun Du, Jun Xu, Yilong Yin, Ling Shao, Cees Snoek	Link	Link
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion	Qinqing Zheng, Jinshuo Dong, Qi Long, Weijie Su	Link	Link
What Can Learned Intrinsic Rewards Capture?	Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado Van Hasselt, David Silver, Satinder Singh	Link	Link
Error-Bounded Correction of Noisy Labels	Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen	Link	Link
Robust Graph Representation Learning via Neural Sparsification	Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang	Link	Link
Bisection-Based Pricing for Repeated Contextual Auctions against Strategic Buyer	Anton Zhiyanov, Alexey Drutsa	Link	Link
Best Arm Identification for Cascading Bandits in the Fixed Confidence Setting	Zixin Zhong, Wang Chi Cheung, Vincent Tan	Link	Link
Neural Contextual Bandits with UCB-based Exploration	Dongruo Zhou, Lihong Li, Quanquan Gu	Link	Link
MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time	Xichuan Zhou, Yicong Peng, Chunqiao Long, Fengbo Ren, Cong Shi	Link	Link
Nonparametric Score Estimators	Yuhao Zhou, Jiaxin Shi, Jun Zhu	Link	Link
Time-Consistent Self-Supervision for Semi-Supervised Learning	Tianyi Zhou, Shengjie Wang, Jeff Bilmes	Link	Link
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support	Yuan Zhou, Hongseok Yang, Yee Whye Teh, Tom Rainforth	Link	Link
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks	Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc Le, Qiang Liu, Dale Schuurmans	Link	Link
Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization	Pan Zhou, Xiao-Tong Yuan	Link	Link
Robust Outlier Arm Identification	Yinglun Zhu, Sumeet Katariya, Robert Nowak	Link	Link
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference	Michael Zhu, Chang Liu, Jun Zhu	Link	Link
Causal Effect Estimation and Optimal Dose Suggestions in Mobile Health	Liangyu Zhu, Wenbin Lu, Rui Song	Link	Link
Thompson Sampling Algorithms for Mean-Variance Bandits	Qiuyu Zhu, Vincent Tan	Link	Link
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization	Sicheng Zhu, Xiao Zhang, David Evans	Link	Link
Linear Convergence of Randomized Primal-Dual Coordinate Method for Large-scale Linear Constrained Convex Programming	Daoli Zhu, Lei Zhao	Link	Link
When Demands Evolve Larger and Noisier: Learning and Earning in a Growing Environment	Feng Zhu, Zeyu Zheng	Link	Link
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE	Juntang Zhuang, Nicha Dvornek, Xiaoxiao Li, Sekhar Tatikonda, Xenophon Papademetris, James Duncan	Link	Link
Learning Optimal Tree Models under Beam Search	Jingwei Zhuo, Ziru Xu, Wei Dai, Han Zhu, Han Li, Jian Xu, Kun Gai	Link	Link
Laplacian Regularized Few-Shot Learning	Imtiaz Ziko, Jose Dolz, Eric Granger, Ismail Ben Ayed	Link	Link
Influenza Forecasting Framework based on Gaussian Processes	Christoph Zimmer, Reza Yaesoubi	Link	Link
A general recurrent state space framework for modeling neural dynamics during decision-making	David Zoltowski, Jonathan Pillow, Scott Linderman	Link	Link
Transformer Hawkes Process	Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha	Link	Link