14 citations · 26 across the 9 of their papers we have counts for
3 papers · 1 filter
On the Reuse Bias in Off-Policy Reinforcement Learning
Chengyang Ying, Zhongkai Hao, Xinning Zhou +3
Importance sampling (IS) is a popular technique in off-policy evaluation, which re-weights the return of trajectories in the replay buffer to boost sample efficiency. However, trai…
Consistent Attack: Universal Adversarial Perturbation on Embodied Vision Navigation
Chengyang Ying, You Qiaoben, Xinning Zhou +3
Embodied agents in vision navigation coupled with deep neural networks have attracted increasing attention. However, deep neural networks have been shown vulnerable to malicious ad…
Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk
Chengyang Ying, Xinning Zhou, Hang Su +3
Though deep reinforcement learning (DRL) has obtained substantial success, it may encounter catastrophic failures due to the intrinsic uncertainty of both transition and observatio…