| 2022 | Trace norm regularization for multi-task learning with scarce data. | Etienne Boursier, Mikhail Konobeev, Nicolas Flammarion |
| 2022 | Gardner formula for Ising perceptron models at small densities. | Erwin Bolthausen, Shuta Nakajima, Nike Sun, Changji Xu |
| 2022 | Smoothed Online Learning is as Easy as Statistical Learning. | Adam Block, Yuval Dagan, Noah Golowich, Alexander Rakhlin |
| 2022 | On the power of adaptivity in statistical adversaries. | Guy Blanc, Jane Lange, Ali Malik, Li-Yang Tan |
| 2022 | Universal Online Learning with Bounded Loss: Reduction to Binary Classification. | Mose Blanchard, Romain Cosson |
| 2022 | Universal Online Learning: an Optimistically Universal Learning Rule. | Mose Blanchard |
| 2022 | On the Benefits of Large Learning Rates for Kernel Methods. | Gaspard Beugnot, Julien Mairal, Alessandro Rudi |
| 2022 | On The Memory Complexity of Uniformity Testing. | Tomer Berg, Or Ordentlich, Ofer Shayevitz |
| 2022 | Derivatives and residual distribution of regularized M-estimators with application to adaptive tuning. | Pierre C. Bellec, Yiwei Shen |
| 2022 | Generalization Bounds for Data-Driven Numerical Linear Algebra. | Peter L. Bartlett, Piotr Indyk, Tal Wagner |
| 2022 | Learning Low Degree Hypergraphs. | Eric Balkanski, Oussama Hanguir, Shatian Wang |
| 2022 | Robustly-reliable learners under poisoning attacks. | Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma |
| 2022 | Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo. | Krishna Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Shunshi Zhang |
| 2022 | Uniform Stability for First-Order Empirical Risk Minimization. | Amit Attia, Tomer Koren |
| 2022 | Hierarchical Clustering in Graph Streams: Single-Pass Algorithms and Space Lower Bounds. | Sepehr Assadi, Vaggos Chatziafratis, Jakub Lacki, Vahab Mirrokni, Chen Wang |
| 2022 | Private and polynomial time algorithms for learning Gaussians and beyond. | Hassan Ashtiani, Christopher Liaw |
| 2022 | From Sampling to Optimization on Discrete Domains with Applications to Determinant Maximization. | Nima Anari, Thuy-Duong Vuong |
| 2022 | Stochastic Variance Reduction for Variational Inequality Methods. | Ahmet Alacaoglu, Yura Malitsky |
| 2022 | Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling. | Alekh Agarwal, Tong Zhang |
| 2022 | Minimax Regret Optimization for Robust Machine Learning under Distribution Shift. | Alekh Agarwal, Tong Zhang |
| 2022 | A Sharp Memory-Regret Trade-off for Multi-Pass Streaming Bandits. | Arpit Agarwal, Sanjeev Khanna, Prathamesh Patil |
| 2022 | Robust Estimation for Random Graphs. | Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang |
| 2022 | The Role of Interactivity in Structured Estimation. | Jayadev Acharya, Clment L. Canonne, Himanshu Tyagi, Ziteng Sun |
| 2022 | The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks. | Emmanuel Abbe, Enric Boix Adser, Theodor Misiakiewicz |
| 2021 | Benign Overfitting of Constant-Stepsize SGD for Linear Regression. | Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Sham M. Kakade |