27 citations · 41 across the 9 of their papers we have counts for
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cs.LG2024★ 9 cited
ACL-QL: Adaptive Conservative Level in Q-Learning for Offline Reinforcement Learning
Kun Wu, Yinuo Zhao, Zhiyuan Xu +5
Offline Reinforcement Learning (RL), which operates solely on static datasets without further interactions with the environment, provides an appealing alternative to learning a saf…
cs.LG2022★ 1 cited
Continual Few-Shot Learning with Adversarial Class Storage
Kun Wu, Chengxiang Yin, Jian Tang +3
Humans have a remarkable ability to quickly and effectively learn new concepts in a continuous manner without forgetting old knowledge. Though deep learning has made tremendous suc…
cs.LG2018★ 27 cited
Adversarial Meta-Learning
Chengxiang Yin, Jian Tang, Zhiyuan Xu +1
Meta-learning enables a model to learn from very limited data to undertake a new task. In this paper, we study the general meta-learning with adversarial samples. We present a meta…