349 citations · 900 across the 26 of their papers we have counts for
Showing 2023 · cs.LGShow all
3 papers · 2 filters
cs.LG2023★ 3 cited
Decoupled Prioritized Resampling for Offline RL
Yang Yue, Bingyi Kang, Xiao Ma +4
Offline reinforcement learning (RL) is challenged by the distributional shift problem. To address this problem, existing works mainly focus on designing sophisticated policy constr…
cs.LG2023★ 1 cited
Improving and Benchmarking Offline Reinforcement Learning Algorithms
Bingyi Kang, Xiao Ma, Yirui Wang +2
Recently, Offline Reinforcement Learning (RL) has achieved remarkable progress with the emergence of various algorithms and datasets. However, these methods usually focus on algori…
cs.LG2023★ 5 cited
Efficient Diffusion Policies for Offline Reinforcement Learning
Bingyi Kang, Xiao Ma, Chao Du +2
Offline reinforcement learning (RL) aims to learn optimal policies from offline datasets, where the parameterization of policies is crucial but often overlooked. Recently, Diffsuio…