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cs.LG2026
Residuals-based Offline Reinforcement Learning
Qing Zhu, Xian Yu
Offline reinforcement learning (RL) has received increasing attention for learning policies from previously collected data without interaction with the real environment, which is p…
cs.LG2025
Reward Redistribution via Gaussian Process Likelihood Estimation
Minheng Xiao, Xian Yu
In many practical reinforcement learning tasks, feedback is only provided at the end of a long horizon, leading to sparse and delayed rewards. Existing reward redistribution method…
cs.LG2024
On the Approximation and Convergence of Distributional Policy Gradient Algorithms for Risk-Sensitive Reinforcement Learning
Minheng Xiao, Xian Yu, Lei Ying
Risk-sensitive reinforcement learning (RL) is crucial for maintaining reliable performance in high-stakes applications. While traditional RL methods aim to learn a point estimate o…