| 2021 | The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities. | Wass Azizian, Franck Iutzeler, Jrme Malick, Panayotis Mertikopoulos |
| 2021 | Adversarially Robust Low Dimensional Representations. | Pranjal Awasthi, Vaggos Chatziafratis, Xue Chen, Aravindan Vijayaraghavan |
| 2021 | Functions with average smoothness: structure, algorithms, and learning. | Yair Ashlagi, Lee-Ad Gottlieb, Aryeh Kontorovich |
| 2021 | Learning in Matrix Games can be Arbitrarily Complex. | Gabriel P. Andrade, Rafael M. Frongillo, Georgios Piliouras |
| 2021 | The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood. | Nima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford |
| 2021 | SGD Generalizes Better Than GD (And Regularization Doesn't Help). | Idan Amir, Tomer Koren, Roi Livni |
| 2021 | Regret Minimization in Heavy-Tailed Bandits. | Shubhada Agrawal, Sandeep Juneja, Wouter M. Koolen |
| 2021 | Open Problem: Are all VC-classes CPAC learnable? | Sushant Agarwal, Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner |
| 2021 | Stochastic block model entropy and broadcasting on trees with survey. | Emmanuel Abbe, Elisabetta Cornacchia, Yuzhou Gu, Yury Polyanskiy |
| 2021 | Softmax Policy Gradient Methods Can Take Exponential Time to Converge. | Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen |
| 2021 | Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries. | Marco Bressan, Nicol Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice |
| 2021 | Learning to Stop with Surprisingly Few Samples. | Daniel Russo, Assaf Zeevi, Tianyi Zhang |
| 2021 | Towards a Query-Optimal and Time-Efficient Algorithm for Clustering with a Faulty Oracle. | Pan Peng, Jiapeng Zhang |
| 2021 | Moment Multicalibration for Uncertainty Estimation. | Christopher Jung, Changhwa Lee, Mallesh M. Pai, Aaron Roth, Rakesh Vohra |
| 2020 | Wasserstein Control of Mirror Langevin Monte Carlo. | Kelvin Shuangjian Zhang, Gabriel Peyr, Jalal Fadili, Marcelo Pereyra |
| 2020 | Nearly Non-Expansive Bounds for Mahalanobis Hard Thresholding. | Xiao-Tong Yuan, Ping Li |
| 2020 | Learning a Single Neuron with Gradient Methods. | Gilad Yehudai, Ohad Shamir |
| 2020 | Non-asymptotic Analysis for Nonparametric Testing. | Yun Yang, Zuofeng Shang, Guang Cheng |
| 2020 | Tree-projected gradient descent for estimating gradient-sparse parameters on graphs. | Sheng Xu, Zhou Fan, Sahand Negahban |
| 2020 | Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium. | Qiaomin Xie, Yudong Chen, Zhaoran Wang, Zhuoran Yang |
| 2020 | Kernel and Rich Regimes in Overparametrized Models. | Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro |
| 2020 | Taking a hint: How to leverage loss predictors in contextual bandits? | Chen-Yu Wei, Haipeng Luo, Alekh Agarwal |
| 2020 | Active Learning for Identification of Linear Dynamical Systems. | Andrew Wagenmaker, Kevin Jamieson |
| 2020 | Balancing Gaussian vectors in high dimension. | Paxton Turner, Raghu Meka, Philippe Rigollet |
| 2020 | Estimation and Inference with Trees and Forests in High Dimensions. | Vasilis Syrgkanis, Manolis Zampetakis |