| 2022 | Lattice-Based Methods Surpass Sum-of-Squares in Clustering. | Ilias Zadik, Min Jae Song, Alexander S. Wein, Joan Bruna |
| 2022 | Mean-field nonparametric estimation of interacting particle systems. | Rentian Yao, Xiaohui Chen, Yun Yang |
| 2022 | Eigenspace Restructuring: A Principle of Space and Frequency in Neural Networks. | Lechao Xiao |
| 2022 | Multi-Agent Learning for Iterative Dominance Elimination: Formal Barriers and New Algorithms. | Jibang Wu, Haifeng Xu, Fan Yao |
| 2022 | Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares. | Blake E. Woodworth, Francis R. Bach, Alessandro Rudi |
| 2022 | Multilevel Optimization for Inverse Problems. | Simon Weissmann, Ashia Wilson, Jakob Zech |
| 2022 | Random Graph Matching in Geometric Models: the Case of Complete Graphs. | Haoyu Wang, Yihong Wu, Jiaming Xu, Israel Yolou |
| 2022 | Beyond No Regret: Instance-Dependent PAC Reinforcement Learning. | Andrew J. Wagenmaker, Max Simchowitz, Kevin Jamieson |
| 2022 | Mirror Descent Strikes Again: Optimal Stochastic Convex Optimization under Infinite Noise Variance. | Nuri Mert Vural, Lu Yu, Krishnakumar Balasubramanian, Stanislav Volgushev, Murat A. Erdogdu |
| 2022 | (Nearly) Optimal Private Linear Regression for Sub-Gaussian Data via Adaptive Clipping. | Prateek Varshney, Abhradeep Thakurta, Prateek Jain |
| 2022 | Accelerated SGD for Non-Strongly-Convex Least Squares. | Aditya Varre, Nicolas Flammarion |
| 2022 | Width is Less Important than Depth in ReLU Neural Networks. | Gal Vardi, Gilad Yehudai, Ohad Shamir |
| 2022 | Learning to Control Linear Systems can be Hard. | Anastasios Tsiamis, Ingvar M. Ziemann, Manfred Morari, Nikolai Matni, George J. Pappas |
| 2022 | Risk bounds for aggregated shallow neural networks using Gaussian priors. | Laura Tinsi, Arnak S. Dalalyan |
| 2022 | Two-Sided Weak Submodularity for Matroid Constrained Optimization and Regression. | Theophile Thiery, Justin Ward |
| 2022 | Stochastic linear optimization never overfits with quadratically-bounded losses on general data. | Matus Telgarsky |
| 2022 | Minimax Regret on Patterns Using Kullback-Leibler Divergence Covering. | Jennifer Tang |
| 2022 | Tracking Most Significant Arm Switches in Bandits. | Joe Suk, Samory Kpotufe |
| 2022 | On characterizations of learnability with computable learners. | Tom F. Sterkenburg |
| 2022 | Self-Consistency of the Fokker Planck Equation. | Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani |
| 2022 | The Implicit Bias of Benign Overfitting. | Ohad Shamir |
| 2022 | Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms. | Milad Sefidgaran, Amin Gohari, Gal Richard, Umut Simsekli |
| 2022 | Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond. | Matan Schliserman, Tomer Koren |
| 2022 | Optimization-Based Separations for Neural Networks. | Itay Safran, Jason D. Lee |
| 2022 | On the Role of Channel Capacity in Learning Gaussian Mixture Models. | Elad Romanov, Tamir Bendory, Or Ordentlich |