| 2024 | Anytime-Constrained Reinforcement Learning. | Jeremy McMahan, Xiaojin Zhu |
| 2024 | An Improved Algorithm for Learning Drifting Discrete Distributions. | Alessio Mazzetto |
| 2024 | Directed Hypergraph Representation Learning for Link Prediction. | Zitong Ma, Wenbo Zhao, Zhe Yang |
| 2024 | Robust Approximate Sampling via Stochastic Gradient Barker Dynamics. | Lorenzo Mauri, Giacomo Zanella |
| 2024 | Acceleration and Implicit Regularization in Gaussian Phase Retrieval. | Tyler Maunu, Martin Molina-Fructuoso |
| 2024 | Achieving Group Distributional Robustness and Minimax Group Fairness with Interpolating Classifiers. | Natalia Martnez, Martn Bertrn, Guillermo Sapiro |
| 2024 | On the Impact of Overparameterization on the Training of a Shallow Neural Network in High Dimensions. | Simon Martin, Francis R. Bach, Giulio Biroli |
| 2024 | Policy Learning for Localized Interventions from Observational Data. | Myrl G. Marmarelis, Fred Morstatter, Aram Galstyan, Greg Ver Steeg |
| 2024 | Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2024 | Consistent Optimal Transport with Empirical Conditional Measures. | Piyushi Manupriya, Rachit Keerti Das, Sayantan Biswas, Saketha Nath Jagarlapudi |
| 2024 | A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning. | Mizhaan Prajit Maniyar, Prashanth L. A., Akash Mondal, Shalabh Bhatnagar |
| 2024 | Identifying Confounding from Causal Mechanism Shifts. | Sarah Mameche, Jilles Vreeken, David Kaltenpoth |
| 2024 | Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits. | Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff |
| 2024 | Multi-Agent Learning in Contextual Games under Unknown Constraints. | Anna M. Maddux, Maryam Kamgarpour |
| 2024 | Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses. | Ziye Ma, Ying Chen, Javad Lavaei, Somayeh Sojoudi |
| 2024 | Inconsistency of Cross-Validation for Structure Learning in Gaussian Graphical Models. | Zhao Lyu, Wai Ming Tai, Mladen Kolar, Bryon Aragam |
| 2024 | Graph Pruning for Enumeration of Minimal Unsatisfiable Subsets. | Panagiotis Lymperopoulos, Liping Liu |
| 2024 | Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach. | Juanwu Lu, Wei Zhan, Masayoshi Tomizuka, Yeping Hu |
| 2024 | DE-HNN: An effective neural model for Circuit Netlist representation. | Zhishang Luo, Truong Son Hy, Puoya Tabaghi, Michal Defferrard, Elahe Rezaei, Ryan Carey, W. Rhett Davis, Rajeev Jain, Yusu Wang |
| 2024 | No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints. | Arpan Losalka, Jonathan Scarlett |
| 2024 | Causal Modeling with Stationary Diffusions. | Lars Lorch, Andreas Krause, Bernhard Schlkopf |
| 2024 | Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. | Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney |
| 2024 | Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition. | Long-Fei Li, Peng Zhao, Zhi-Hua Zhou |
| 2024 | On Convergence in Wasserstein Distance and f-divergence Minimization Problems. | Cheuk Ting Li, Jingwei Zhang, Farzan Farnia |
| 2024 | Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach. | Yinan Li, Chicheng Zhang |