3 citations · 9 across the 6 of their papers we have counts for
6 papers
Supported Trust Region Optimization for Offline Reinforcement Learning
Yixiu Mao, Hongchang Zhang, Chen Chen +2
Offline reinforcement learning suffers from the out-of-distribution issue and extrapolation error. Most policy constraint methods regularize the density of the trained policy towar…
State-Aware Proximal Pessimistic Algorithms for Offline Reinforcement Learning
Chen Chen, Hongyao Tang, Yi Ma +4
Pessimism is of great importance in offline reinforcement learning (RL). One broad category of offline RL algorithms fulfills pessimism by explicit or implicit behavior regularizat…
Rethinking Reinforcement Learning based Logic Synthesis
Chao Wang, Chen Chen, Dong Li +1
Recently, reinforcement learning has been used to address logic synthesis by formulating the operator sequence optimization problem as a Markov decision process. However, through e…
Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward Machines
Xuejing Zheng, Chao Yu, Chen Chen +2
Continuously learning new tasks using high-level ideas or knowledge is a key capability of humans. In this paper, we propose Lifelong reinforcement learning with Sequential linear…
CMML: Contextual Modulation Meta Learning for Cold-Start Recommendation
Xidong Feng, Chen Chen, Dong Li +3
Practical recommender systems experience a cold-start problem when observed user-item interactions in the history are insufficient. Meta learning, especially gradient based one, ca…
MGHRL: Meta Goal-generation for Hierarchical Reinforcement Learning
Haotian Fu, Hongyao Tang, Jianye Hao +2
Most meta reinforcement learning (meta-RL) methods learn to adapt to new tasks by directly optimizing the parameters of policies over primitive action space. Such algorithms work w…