4 citations · 4 across the 1 of their papers we have counts for
2 papers
cs.LG2022★ 4 cited
Reinforcement Learning with Automated Auxiliary Loss Search
Tairan He, Yuge Zhang, Kan Ren +5
A good state representation is crucial to solving complicated reinforcement learning (RL) challenges. Many recent works focus on designing auxiliary losses for learning informative…
cs.LG2020
Energy-Based Imitation Learning
Minghuan Liu, Tairan He, Minkai Xu +1
We tackle a common scenario in imitation learning (IL), where agents try to recover the optimal policy from expert demonstrations without further access to the expert or environmen…