ML Anthology

Shi, Laixi

20 publications

ICML 2025 Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning Laixi Shi, Jingchu Gai, Eric Mazumdar, Yuejie Chi, Adam Wierman
AISTATS 2025 Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency from Shifted-Dynamics Data Chengrui Qu, Laixi Shi, Kishan Panaganti, Pengcheng You, Adam Wierman
ICML 2025 Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization Chenbei Lu, Laixi Shi, Zaiwei Chen, Chenye Wu, Adam Wierman
ICLR 2025 Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning Shangding Gu, Laixi Shi, Muning Wen, Ming Jin, Eric Mazumdar, Yuejie Chi, Adam Wierman, Costas Spanos
NeurIPS 2025 SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer Yarden As, Chengrui Qu, Benjamin Unger, Dongho Kang, Max van der Hart, Laixi Shi, Stelian Coros, Adam Wierman, Andreas Krause
ICLR 2025 Tractable Multi-Agent Reinforcement Learning Through Behavioral Economics Eric Mazumdar, Kishan Panaganti, Laixi Shi
NeurIPSW 2024 A Behavioral Economics Approach to Principled Multi-Agent Reinforcement Learning Eric Mazumdar, Kishan Panaganti, Laixi Shi
NeurIPS 2024 BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-Based Reinforcement Learning Haohong Lin, Wenhao Ding, Jian Chen, Laixi Shi, Jiacheng Zhu, Bo Li, Ding Zhao
JMLR 2024 Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity Laixi Shi, Yuejie Chi
NeurIPS 2024 Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation Shangding Gu, Laixi Shi, Yuhao Ding, Alois Knoll, Costas Spanos, Adam Wierman, Ming Jin
ICML 2024 Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie Chi
NeurIPS 2024 Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms Pierre Clavier, Laixi Shi, Erwan Le Pennec, Eric Mazumdar, Adam Wierman, Matthieu Geist
ICML 2024 Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty Laixi Shi, Eric Mazumdar, Yuejie Chi, Adam Wierman
UAI 2023 A Trajectory Is Worth Three Sentences: Multimodal Transformer for Offline Reinforcement Learning Yiqi Wang, Mengdi Xu, Laixi Shi, Yuejie Chi
ECML-PKDD 2023 Offline Reinforcement Learning with On-Policy Q-Function Regularization Laixi Shi, Robert Dadashi, Yuejie Chi, Pablo Samuel Castro, Matthieu Geist
NeurIPS 2023 Seeing Is Not Believing: Robust Reinforcement Learning Against Spurious Correlation Wenhao Ding, Laixi Shi, Yuejie Chi, Ding Zhao
NeurIPS 2023 The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi
NeurIPS 2022 Curriculum Reinforcement Learning Using Optimal Transport via Gradual Domain Adaptation Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao
ICML 2022 Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi
NeurIPS 2021 Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning Gen Li, Laixi Shi, Yuxin Chen, Yuantao Gu, Yuejie Chi