| 2024 | Extragradient Type Methods for Riemannian Variational Inequality Problems. | Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao |
| 2024 | Directional Optimism for Safe Linear Bandits. | Spencer Hutchinson, Berkay Turan, Mahnoosh Alizadeh |
| 2024 | Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations. | Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao |
| 2024 | Generalization Bounds for Label Noise Stochastic Gradient Descent. | Jung Eun Huh, Patrick Rebeschini |
| 2024 | Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications. | Jie Hu, Vishwaraj Doshi, Do Young Eun |
| 2024 | Parameter-Agnostic Optimization under Relaxed Smoothness. | Florian Hbler, Junchi Yang, Xiang Li, Niao He |
| 2024 | On the Statistical Efficiency of Mean-Field Reinforcement Learning with General Function Approximation. | Jiawei Huang, Batuhan Yardim, Niao He |
| 2024 | Adaptive Federated Minimax Optimization with Lower Complexities. | Feihu Huang, Xinrui Wang, Junyi Li, Songcan Chen |
| 2024 | Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation. | Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang |
| 2024 | Surrogate Bayesian Networks for Approximating Evolutionary Games. | Vincent Hsiao, Dana S. Nau, Bobak Pezeshki, Rina Dechter |
| 2024 | Fast 1-Wasserstein distance approximations using greedy strategies. | Guillaume Houry, Han Bao, Han Zhao, Makoto Yamada |
| 2024 | Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds. | Alexandra Maria Hotti, Lennart Alexander Van der Goten, Jens Lagergren |
| 2024 | The ALℓ | John Hood, Aaron J. Schein |
| 2024 | A Primal-Dual-Critic Algorithm for Offline Constrained Reinforcement Learning. | Kihyuk Hong, Yuhang Li, Ambuj Tewari |
| 2024 | Robust variance-regularized risk minimization with concomitant scaling. | Matthew J. Holland |
| 2024 | Boundary-Aware Uncertainty for Feature Attribution Explainers. | Davin Hill, Aria Masoomi, Max Torop, Sandesh Ghimire, Jennifer G. Dy |
| 2024 | Adaptive Discretization for Event PredicTion (ADEPT). | Jimmy Hickey, Ricardo Henao, Daniel Wojdyla, Michael J. Pencina, Matthew Engelhard |
| 2024 | TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression. | Zelin He, Ying Sun, Runze Li |
| 2024 | Sample Efficient Learning of Factored Embeddings of Tensor Fields. | Taemin Heo, Chandrajit Bajaj |
| 2024 | The Relative Gaussian Mechanism and its Application to Private Gradient Descent. | Hadrien Hendrikx, Paul Mangold, Aurlien Bellet |
| 2024 | Comparing Comparators in Generalization Bounds. | Fredrik Hellstrm, Benjamin Guedj |
| 2024 | A 4-Approximation Algorithm for Min Max Correlation Clustering. | Holger S. G. Heidrich, Jannik Irmai, Bjoern Andres |
| 2024 | Adaptive Parametric Prototype Learning for Cross-Domain Few-Shot Classification. | Marzi Heidari, Abdullah Alchihabi, Qing En, Yuhong Guo |
| 2024 | Compression with Exact Error Distribution for Federated Learning. | Mahmoud Hegazy, Rmi Leluc, Cheuk Ting Li, Aymeric Dieuleveut |
| 2024 | Estimating treatment effects from single-arm trials via latent-variable modeling. | Manuel Haussmann, Tran Minh Son Le, Viivi Halla-aho, Samu Kurki, Jussi Leinonen, Miika Koskinen, Samuel Kaski, Harri Lhdesmki |