| 2021 | A Deep Conditioning Treatment of Neural Networks. | Naman Agarwal, Pranjal Awasthi, Satyen Kale |
| 2021 | Stochastic Dueling Bandits with Adversarial Corruption. | Arpit Agarwal, Shivani Agarwal, Prathamesh Patil |
| 2021 | On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians. | Ishaq Aden-Ali, Hassan Ashtiani, Gautam Kamath |
| 2021 | Intervention Efficient Algorithms for Approximate Learning of Causal Graphs. | Raghavendra Addanki, Andrew McGregor, Cameron Musco |
| 2021 | Efficient Algorithms for Stochastic Repeated Second-price Auctions. | Juliette Achddou, Olivier Capp, Aurlien Garivier |
| 2021 | Differentially Private Assouad, Fano, and Le Cam. | Jayadev Acharya, Ziteng Sun, Huanyu Zhang |
| 2021 | Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints. | Jayadev Acharya, Peter Kairouz, Yuhan Liu, Ziteng Sun |
| 2021 | Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization. | Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono |
| 2021 | Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance. | Jie Shen, Chicheng Zhang |
| 2021 | Efficient sampling from the Bingham distribution. | Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski |
| 2021 | Testing Product Distributions: A Closer Look. | Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, N. V. Vinodchandran |
| 2020 | Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies. | Tom Zahavy, Avinatan Hassidim, Haim Kaplan, Yishay Mansour |
| 2020 | Mixing Time Estimation in Ergodic Markov Chains from a Single Trajectory with Contraction Methods. | Geoffrey Wolfer |
| 2020 | Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling. | Cindy Trinh, Emilie Kaufmann, Claire Vernade, Richard Combes |
| 2020 | Online Non-Convex Learning: Following the Perturbed Leader is Optimal. | Arun Sai Suggala, Praneeth Netrapalli |
| 2020 | Approximate Representer Theorems in Non-reflexive Banach Spaces. | Kevin Schlegel |
| 2020 | Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions. | Charles Riou, Junya Honda |
| 2020 | Top- | Idan Rejwan, Yishay Mansour |
| 2020 | Finding Robust Nash equilibria. | Vianney Perchet |
| 2020 | Efficient Private Algorithms for Learning Large-Margin Halfspaces. | Huy Le Nguyen, Jonathan R. Ullman, Lydia Zakynthinou |
| 2020 | Privately Answering Classification Queries in the Agnostic PAC Model. | Anupama Nandi, Raef Bassily |
| 2020 | A Non-Trivial Algorithm Enumerating Relevant Features over Finite Fields. | Mikito Nanashima |
| 2020 | On the Analysis of EM for truncated mixtures of two Gaussians. | Sai Ganesh Nagarajan, Ioannis Panageas |
| 2020 | Toward universal testing of dynamic network models. | Abram Magner, Wojciech Szpankowski |
| 2020 | Feedback graph regret bounds for Thompson Sampling and UCB. | Thodoris Lykouris, va Tardos, Drishti Wali |