| 2024 | Best Arm Identification with Resource Constraints. | Zitian Li, Wang Chi Cheung |
| 2024 | Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression. | Kevin Li, Max Balakirsky, Simon Mak |
| 2024 | Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures. | Hao Liang, Zhiquan Luo |
| 2024 | Multi-Resolution Active Learning of Fourier Neural Operators. | Shibo Li, Xin Yu, Wei W. Xing, Robert M. Kirby, Akil Narayan, Shandian Zhe |
| 2024 | Computing epidemic metrics with edge differential privacy. | George Z. Li, Dung Nguyen, Anil Vullikanti |
| 2024 | Any-dimensional equivariant neural networks. | Eitan Levin, Mateo Daz |
| 2024 | Optimal Transport for Measures with Noisy Tree Metric. | Tam Le, Truyen Nguyen, Kenji Fukumizu |
| 2024 | Graph fission and cross-validation. | James Leiner, Aaditya Ramdas |
| 2024 | Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion. | Junghyun Lee, Se-Young Yun, Kwang-Sung Jun |
| 2024 | XB-MAML: Learning Expandable Basis Parameters for Effective Meta-Learning with Wide Task Coverage. | Jae-Jun Lee, Sung Whan Yoon |
| 2024 | Approximate Bayesian Class-Conditional Models under Continuous Representation Shift. | Thomas L. Lee, Amos J. Storkey |
| 2024 | Analysis of Using Sigmoid Loss for Contrastive Learning. | Chungpa Lee, Joonhwan Chang, Jy-yong Sohn |
| 2024 | Queuing dynamics of asynchronous Federated Learning. | Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines |
| 2024 | On the Privacy of Selection Mechanisms with Gaussian Noise. | Jonathan Lebensold, Doina Precup, Borja Balle |
| 2024 | Conditional Adjustment in a Markov Equivalence Class. | Sara LaPlante, Emilija Perkovic |
| 2024 | Causal Q-Aggregation for CATE Model Selection. | Hui Lan, Vasilis Syrgkanis |
| 2024 | Sharpened Lazy Incremental Quasi-Newton Method. | Aakash Sunil Lahoti, Spandan Senapati, Ketan Rajawat, Alec Koppel |
| 2024 | Tackling the XAI Disagreement Problem with Regional Explanations. | Gabriel Laberge, Yann Batiste Pequignot, Mario Marchand, Foutse Khomh |
| 2024 | Efficient Low-Dimensional Compression of Overparameterized Models. | Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, Qing Qu |
| 2024 | Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable. | Hyeok Kyu Kwon, Minwoo Chae |
| 2024 | Variational Resampling. | Oskar Kviman, Nicola Branchini, Vctor Elvira, Jens Lagergren |
| 2024 | Best-of-Both-Worlds Algorithms for Linear Contextual Bandits. | Yuko Kuroki, Alberto Rumi, Taira Tsuchiya, Fabio Vitale, Nicol Cesa-Bianchi |
| 2024 | Functional Graphical Models: Structure Enables Offline Data-Driven Optimization. | Kuba Grudzien Kuba, Masatoshi Uehara, Sergey Levine, Pieter Abbeel |
| 2024 | Unveiling Latent Causal Rules: A Temporal Point Process Approach for Abnormal Event Explanation. | Yiling Kuang, Chao Yang, Yang Yang, Shuang Li |
| 2024 | Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective. | Sanath Kumar Krishnamurthy, Adrienne Margaret Propp, Susan Athey |