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Papers
A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
ICML 2025
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
AISTATS 2024
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms
NeurIPS 2024
Model-Free Robust Reinforcement Learning with Sample Complexity Analysis
UAI 2024
Near-Optimal Distributionally Robust Reinforcement Learning with General L_p Norms
NeurIPS 2024
Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning
AISTATS 2023