15 citations · 43 across the 10 of their papers we have counts for
6 papers · 1 filter
Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization
Shixuan Liu, Yanghe Feng, Keyu Wu +3
In many domains of empirical sciences, discovering the causal structure within variables remains an indispensable task. Recently, to tackle with unoriented edges or latent assumpti…
A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm
Qi Wang, Yiqin Lv, Yanghe Feng +2
Meta learning is a promising paradigm to enable skill transfer across tasks. Most previous methods employ the empirical risk minimization principle in optimization. However, the re…
PTR-PPO: Proximal Policy Optimization with Prioritized Trajectory Replay
Xingxing Liang, Yang Ma, Yanghe Feng +1
On-policy deep reinforcement learning algorithms have low data utilization and require significant experience for policy improvement. This paper proposes a proximal policy optimiza…
HpGAN: Sequence Search with Generative Adversarial Networks
Mingxing Zhang, Zhengchun Zhou, Lanping Li +3
Sequences play an important role in many engineering applications and systems. Searching sequences with desired properties has long been an interesting but also challenging researc…
Deep Multi-View Spatiotemporal Virtual Graph Neural Network for Significant Citywide Ride-hailing Demand Prediction
Guangyin Jin, Zhexu Xi, Hengyu Sha +2
Urban ride-hailing demand prediction is a crucial but challenging task for intelligent transportation system construction. Predictable ride-hailing demand can facilitate more reaso…
VMAV-C: A Deep Attention-based Reinforcement Learning Algorithm for Model-based Control
Xingxing Liang, Qi Wang, Yanghe Feng +2
Recent breakthroughs in Go play and strategic games have witnessed the great potential of reinforcement learning in intelligently scheduling in uncertain environment, but some bott…