| 2023 | Bayesian Variable Selection in a Million Dimensions. | Martin Jankowiak |
| 2023 | Online Learning for Traffic Routing under Unknown Preferences. | Devansh Jalota, Karthik Gopalakrishnan, Navid Azizan, Ramesh Johari, Marco Pavone |
| 2023 | Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation. | Garud Iyengar, Henry Lam, Tianyu Wang |
| 2023 | Representation Learning in Deep RL via Discrete Information Bottleneck. | Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb |
| 2023 | Kernel Conditional Moment Constraints for Confounding Robust Inference. | Kei Ishikawa, Niao He |
| 2023 | A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets. | Hideaki Ishibashi, Masayuki Karasuyama, Ichiro Takeuchi, Hideitsu Hino |
| 2023 | Learning Constrained Structured Spaces with Application to Multi-Graph Matching. | Hedda Cohen Indelman, Tamir Hazan |
| 2023 | Stochastic Mirror Descent for Large-Scale Sparse Recovery. | Sasila Ilandarideva, Yannis Bekri, Anatoli B. Juditsky, Vianney Perchet |
| 2023 | Fast Block Coordinate Descent for Non-Convex Group Regularizations. | Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai |
| 2023 | Privacy-preserving Sparse Generalized Eigenvalue Problem. | Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang |
| 2023 | Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions. | Zeshan M. Hussain, Ming-Chieh Shih, Michael Oberst, Ilker Demirel, David A. Sontag |
| 2023 | A Tighter Problem-Dependent Regret Bound for Risk-Sensitive Reinforcement Learning. | Xiaoyan Hu, Ho-fung Leung |
| 2023 | Tight Regret and Complexity Bounds for Thompson Sampling via Langevin Monte Carlo. | Tom Huix, Matthew Zhang, Alain Durmus |
| 2023 | AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. | Feihu Huang, Xidong Wu, Zhengmian Hu |
| 2023 | Fix-A-Step: Semi-supervised Learning From Uncurated Unlabeled Data. | Zhe Huang, Mary-Joy Sidhom, Benjamin Wessler, Michael C. Hughes |
| 2023 | Towards Balanced Representation Learning for Credit Policy Evaluation. | Yiyan Huang, Cheuk Hang Leung, Shumin Ma, Zhiri Yuan, Qi Wu, Siyi Wang, Dongdong Wang, Zhixiang Huang |
| 2023 | Delayed Feedback in Generalised Linear Bandits Revisited. | Benjamin Howson, Ciara Pike-Burke, Sarah Filippi |
| 2023 | Optimism and Delays in Episodic Reinforcement Learning. | Benjamin Howson, Ciara Pike-Burke, Sarah Filippi |
| 2023 | Variational Inference for Neyman-Scott Processes. | Chengkuan Hong, Christian R. Shelton |
| 2023 | An Optimization-based Algorithm for Non-stationary Kernel Bandits without Prior Knowledge. | Kihyuk Hong, Yuhang Li, Ambuj Tewari |
| 2023 | Neural Laplace Control for Continuous-time Delayed Systems. | Samuel Holt, Alihan Hyk, Zhaozhi Qian, Hao Sun, Mihaela van der Schaar |
| 2023 | Flexible risk design using bi-directional dispersion. | Matthew J. Holland |
| 2023 | ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images. | Matthew D. Hoffman, Tuan Anh Le, Pavel Sountsov, Christopher Suter, Ben Lee, Vikash K. Mansinghka, Rif A. Saurous |
| 2023 | Unifying local and global model explanations by functional decomposition of low dimensional structures. | Munir Hiabu, Joseph T. Meyer, Marvin N. Wright |
| 2023 | Fast Distributed k-Means with a Small Number of Rounds. | Tom Hess, Ron Visbord, Sivan Sabato |