| 2024 | On the Model-Misspecification in Reinforcement Learning. | Yunfan Li, Lin Yang |
| 2024 | Efficient Neural Architecture Design via Capturing Architecture-Performance Joint Distribution. | Yue Liu, Ziyi Yu, Zitu Liu, Wenjie Tian |
| 2024 | Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation. | Zhishuai Liu, Pan Xu |
| 2024 | Enhancing Distributional Stability among Sub-populations. | Jiashuo Liu, Jiayun Wu, Jie Peng, Xiaoyu Wu, Yang Zheng, Bo Li, Peng Cui |
| 2024 | Proximal Causal Inference for Synthetic Control with Surrogates. | Jizhou Liu, Eric Tchetgen Tchetgen, Carlos Varjo |
| 2024 | Fitting ARMA Time Series Models without Identification: A Proximal Approach. | Yin Liu, Sam Davanloo Tajbakhsh |
| 2024 | Mitigating Underfitting in Learning to Defer with Consistent Losses. | Shuqi Liu, Yuzhou Cao, Qiaozhen Zhang, Lei Feng, Bo An |
| 2024 | Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural Networks. | Kaiting Liu, Zahra Atashgahi, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu |
| 2024 | User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates. | Daogao Liu, Hilal Asi |
| 2024 | Unified Transfer Learning in High-Dimensional Linear Regression. | Shuo Shuo Liu |
| 2024 | Personalized Federated X-armed Bandit. | Wenjie Li, Qifan Song, Jean Honorio |
| 2024 | How Good is a Single Basin? | Kai Lion, Lorenzo Noci, Thomas Hofmann, Gregor Bachmann |
| 2024 | DNNLasso: Scalable Graph Learning for Matrix-Variate Data. | Meixia Lin, Yangjing Zhang |
| 2024 | Learning Safety Constraints from Demonstrations with Unknown Rewards. | David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause |
| 2024 | A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport. | Tianyi Lin, Marco Cuturi, Michael I. Jordan |
| 2024 | Non-Neighbors Also Matter to Kriging: A New Contrastive-Prototypical Learning. | Zhishuai Li, Yunhao Nie, Ziyue Li, Lei Bai, Yisheng Lv, Rui Zhao |
| 2024 | On Ranking-based Tests of Independence. | Myrto Limnios, Stphan Clmenon |
| 2024 | Pathwise Explanation of ReLU Neural Networks. | Seongwoo Lim, Won Jo, Joohyung Lee, Jaesik Choi |
| 2024 | When No-Rejection Learning is Consistent for Regression with Rejection. | Xiaocheng Li, Shang Liu, Chunlin Sun, Hanzhao Wang |
| 2024 | Backward Filtering Forward Deciding in Linear Non-Gaussian State Space Models. | Yunpeng Li, Hans-Andrea Loeliger |
| 2024 | Prior-dependent analysis of posterior sampling reinforcement learning with function approximation. | Yingru Li, Zhi-Quan Luo |
| 2024 | Optimal Exploration is no harder than Thompson Sampling. | Zhaoqi Li, Kevin Jamieson, Lalit Jain |
| 2024 | Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis. | Zihao Li, Xiang Ji, Minshuo Chen, Mengdi Wang |
| 2024 | Mechanics of Next Token Prediction with Self-Attention. | Yingcong Li, Yixiao Huang, Muhammed Emrullah Ildiz, Ankit Singh Rawat, Samet Oymak |
| 2024 | Ethics in Action: Training Reinforcement Learning Agents for Moral Decision-making In Text-based Adventure Games. | Weichen Li, Rati Devidze, Waleed Mustafa, Sophie Fellenz |