3 citations · 6 across the 4 of their papers we have counts for
4 papers
Flow to Control: Offline Reinforcement Learning with Lossless Primitive Discovery
Yiqin Yang, Hao Hu, Wenzhe Li +4
Offline reinforcement learning (RL) enables the agent to effectively learn from logged data, which significantly extends the applicability of RL algorithms in real-world scenarios…
Leveraging Graph-based Cross-modal Information Fusion for Neural Sign Language Translation
Jiangbin Zheng, Siyuan Li, Cheng Tan +3
Sign Language (SL), as the mother tongue of the deaf community, is a special visual language that most hearing people cannot understand. In recent years, neural Sign Language Trans…
CUP: Critic-Guided Policy Reuse
Jin Zhang, Siyuan Li, Chongjie Zhang
The ability to reuse previous policies is an important aspect of human intelligence. To achieve efficient policy reuse, a Deep Reinforcement Learning (DRL) agent needs to decide wh…
Are Gradients on Graph Structure Reliable in Gray-box Attacks?
Zihan Liu, Yun Luo, Lirong Wu +3
Graph edge perturbations are dedicated to damaging the prediction of graph neural networks by modifying the graph structure. Previous gray-box attackers employ gradients from the s…