1 code implementation • 12 Mar 2024 • Chengxing Jia, Fuxiang Zhang, Yi-Chen Li, Chen-Xiao Gao, Xu-Hui Liu, Lei Yuan, Zongzhang Zhang, Yang Yu
Specifically, the objective of adversarial data augmentation is not merely to generate data analogous to offline data distribution; instead, it aims to create adversarial examples designed to confound learned task representations and lead to incorrect task identification.
1 code implementation • 3 Mar 2023 • Xu-Hui Liu, Feng Xu, Xinyu Zhang, Tianyuan Liu, Shengyi Jiang, Ruifeng Chen, Zongzhang Zhang, Yang Yu
In this paper, we propose a novel active imitation learning framework based on a teacher-student interaction model, in which the teacher's goal is to identify the best teaching behavior and actively affect the student's learning process.
no code implementations • 4 Jun 2022 • Xue-Kun Jin, Xu-Hui Liu, Shengyi Jiang, Yang Yu
Value function estimation is an indispensable subroutine in reinforcement learning, which becomes more challenging in the offline setting.
1 code implementation • NeurIPS 2021 • Xu-Hui Liu, Zhenghai Xue, Jing-Cheng Pang, Shengyi Jiang, Feng Xu, Yang Yu
In reinforcement learning, experience replay stores past samples for further reuse.