| 2022 | AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning. | Jihun Yun, Aurlie C. Lozano, Eunho Yang |
| 2022 | Optimal partition recovery in general graphs. | Yi Yu, Oscar Hernan Madrid Padilla, Alessandro Rinaldo |
| 2022 | Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization. | Yaodong Yu, Tianyi Lin, Eric V. Mazumdar, Michael I. Jordan |
| 2022 | Learning from Multiple Noisy Partial Labelers. | Peilin Yu, Tiffany Ding, Stephen H. Bach |
| 2022 | A general sample complexity analysis of vanilla policy gradient. | Rui Yuan, Robert M. Gower, Alessandro Lazaric |
| 2022 | Robust Probabilistic Time Series Forecasting. | Taeho Yoon, Youngsuk Park, Ernest K. Ryu, Yuyang Wang |
| 2022 | Doubly Mixed-Effects Gaussian Process Regression. | Jun Ho Yoon, Daniel P. Jeong, Seyoung Kim |
| 2022 | A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization. | Donghao Ying, Yuhao Ding, Javad Lavaei |
| 2022 | Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations. | Chih-Kuan Yeh, Kuan-Yun Lee, Frederick Liu, Pradeep Ravikumar |
| 2022 | Equivariance Discovery by Learned Parameter-Sharing. | Raymond A. Yeh, Yuan-Ting Hu, Mark Hasegawa-Johnson, Alexander G. Schwing |
| 2022 | Margin-distancing for safe model explanation. | Tom Yan, Chicheng Zhang |
| 2022 | Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity. | Junchi Yang, Antonio Orvieto, Aurlien Lucchi, Niao He |
| 2022 | Offline Policy Selection under Uncertainty. | Mengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans |
| 2022 | Factorization Approach for Low-complexity Matrix Completion Problems: Exponential Number of Spurious Solutions and Failure of Gradient Methods. | Baturalp Yalcin, Haixiang Zhang, Javad Lavaei, Somayeh Sojoudi |
| 2022 | Calibration Error for Heterogeneous Treatment Effects. | Yizhe Xu, Steve Yadlowsky |
| 2022 | Towards Agnostic Feature-based Dynamic Pricing: Linear Policies vs Linear Valuation with Unknown Noise. | Jianyu Xu, Yu-Xiang Wang |
| 2022 | Data Appraisal Without Data Sharing. | Xinlei Xu, Awni Y. Hannun, Laurens van der Maaten |
| 2022 | Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations. | Winnie Xu, Ricky T. Q. Chen, Xuechen Li, David Duvenaud |
| 2022 | Standardisation-function Kernel Stein Discrepancy: A Unifying View on Kernel Stein Discrepancy Tests for Goodness-of-fit. | Wenkai Xu |
| 2022 | Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. | Yue Xing, Qifan Song, Guang Cheng |
| 2022 | The Curse of Passive Data Collection in Batch Reinforcement Learning. | Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvri |
| 2022 | Tile Networks: Learning Optimal Geometric Layout for Whole-page Recommendation. | Shuai Xiao, Zaifan Jiang, Shuang Yang |
| 2022 | Variational Gaussian Processes: A Functional Analysis View. | George Wynne, Veit Wild |
| 2022 | Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation. | Yue Wu, Dongruo Zhou, Quanquan Gu |
| 2022 | Asymptotically Optimal Locally Private Heavy Hitters via Parameterized Sketches. | Hao Wu, Anthony Wirth |