| 2021 | Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective. | Dylan J. Foster, Alexander Rakhlin, David Simchi-Levi, Yunzong Xu |
| 2021 | Convergence rates and approximation results for SGD and its continuous-time counterpart. | Xavier Fontaine, Valentin De Bortoli, Alain Durmus |
| 2021 | Sequential prediction under log-loss and misspecification. | Meir Feder, Yury Polyanskiy |
| 2021 | Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks. | Cong Fang, Jason D. Lee, Pengkun Yang, Tong Zhang |
| 2021 | Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization. | Mathieu Even, Laurent Massouli |
| 2021 | Adaptivity in Adaptive Submodularity. | Hossein Esfandiari, Amin Karbasi, Vahab S. Mirrokni |
| 2021 | Robust Online Convex Optimization in the Presence of Outliers. | Tim van Erven, Sarah Sachs, Wouter M. Koolen, Wojciech Kotlowski |
| 2021 | On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness. | Murat A. Erdogdu, Rasa Hosseinzadeh |
| 2021 | Non-asymptotic approximations of neural networks by Gaussian processes. | Ronen Eldan, Dan Mikulincer, Tselil Schramm |
| 2021 | Kernel Thinning. | Raaz Dwivedi, Lester Mackey |
| 2021 | On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning. | Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai |
| 2021 | Random Coordinate Langevin Monte Carlo. | Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen J. Wright |
| 2021 | Outlier-Robust Learning of Ising Models Under Dobrushin's Condition. | Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart, Yuxin Sun |
| 2021 | The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model. | Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis |
| 2021 | Agnostic Proper Learning of Halfspaces under Gaussian Marginals. | Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis |
| 2021 | The Sample Complexity of Robust Covariance Testing. | Ilias Diakonikolas, Daniel M. Kane |
| 2021 | Boosting in the Presence of Massart Noise. | Ilias Diakonikolas, Russell Impagliazzo, Daniel M. Kane, Rex Lei, Jessica Sorrell, Christos Tzamos |
| 2021 | Weak learning convex sets under normal distributions. | Anindya De, Rocco A. Servedio |
| 2021 | Sparse sketches with small inversion bias. | Michal Derezinski, Zhenyu Liao, Edgar Dobriban, Michael W. Mahoney |
| 2021 | Learning sparse mixtures of permutations from noisy information. | Anindya De, Ryan O'Donnell, Rocco A. Servedio |
| 2021 | A Statistical Taylor Theorem and Extrapolation of Truncated Densities. | Constantinos Daskalakis, Vasilis Kontonis, Christos Tzamos, Emmanouil Zampetakis |
| 2021 | From Local Pseudorandom Generators to Hardness of Learning. | Amit Daniely, Gal Vardi |
| 2021 | Quantifying Variational Approximation for Log-Partition Function. | Romain Cosson, Devavrat Shah |
| 2021 | Online Markov Decision Processes with Aggregate Bandit Feedback. | Alon Cohen, Haim Kaplan, Tomer Koren, Yishay Mansour |
| 2021 | Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm. | Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet |