10 citations · 16 across the 4 of their papers we have counts for
6 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…
Offline Reinforcement Learning with Value-based Episodic Memory
Xiaoteng Ma, Yiqin Yang, Hao Hu +5
Offline reinforcement learning (RL) shows promise of applying RL to real-world problems by effectively utilizing previously collected data. Most existing offline RL algorithms use…
VA-GCN: A Vector Attention Graph Convolution Network for learning on Point Clouds
Haotian Hu, Fanyi Wang, Huixiao Le
Owing to the development of research on local aggregation operators, dramatic breakthrough has been made in point cloud analysis models. However, existing local aggregation operato…
Dissecting Click Fraud Autonomy in the Wild
Tong Zhu, Yan Meng, Haotian Hu +3
Although the use of pay-per-click mechanisms stimulates the prosperity of the mobile advertisement network, fraudulent ad clicks result in huge financial losses for advertisers. Ex…
Generalizable Episodic Memory for Deep Reinforcement Learning
Hao Hu, Jianing Ye, Guangxiang Zhu +2
Episodic memory-based methods can rapidly latch onto past successful strategies by a non-parametric memory and improve sample efficiency of traditional reinforcement learning. Howe…
First-Take-All: Temporal Order-Preserving Hashing for 3D Action Videos
Jun Ye, Hao Hu, Kai Li +2
With the prevalence of the commodity depth cameras, the new paradigm of user interfaces based on 3D motion capturing and recognition have dramatically changed the way of interactio…