no code implementations • 4 Apr 2024 • Kaichen Huang, Minghao Shao, Shenghua Wan, Hai-Hang Sun, Shuai Feng, Le Gan, De-Chuan Zhan
In many real-world visual Imitation Learning (IL) scenarios, there is a misalignment between the agent's and the expert's perspectives, which might lead to the failure of imitation.
no code implementations • 4 Apr 2024 • Kaichen Huang, Hai-Hang Sun, Shenghua Wan, Minghao Shao, Shuai Feng, Le Gan, De-Chuan Zhan
Imitating skills from low-quality datasets, such as sub-optimal demonstrations and observations with distractors, is common in real-world applications.
no code implementations • 15 Mar 2024 • Yucen Wang, Shenghua Wan, Le Gan, Shuai Feng, De-Chuan Zhan
Model-based methods have significantly contributed to distinguishing task-irrelevant distractors for visual control.
1 code implementation • 17 Jun 2022 • Xin-Chun Li, Jin-Lin Tang, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, Le Gan, De-Chuan Zhan
Federated KWS (FedKWS) could serve as a solution without directly sharing users' data.
no code implementations • 26 Jul 2021 • Xin-Chun Li, Le Gan, De-Chuan Zhan, Yunfeng Shao, Bingshuai Li, Shaoming Song
We advocate the proposed methods could serve as a preliminary try to explore where to privatize for a novel non-iid scene.
1 code implementation • NeurIPS 2021 • Su Lu, Han-Jia Ye, Le Gan, De-Chuan Zhan
Different from $\mathcal{S}$/$\mathcal{Q}$ protocol, we can also evaluate a task-specific solver by comparing it to a target model $\mathcal{T}$, which is the optimal model for this task or a model that behaves well enough on this task ($\mathcal{S}$/$\mathcal{T}$ protocol).