5 citations · 6 across the 3 of their papers we have counts for
4 papers
Expanding Semantic Knowledge for Zero-shot Graph Embedding
Zheng Wang, Ruihang Shao, Changping Wang +3
Zero-shot graph embedding is a major challenge for supervised graph learning. Although a recent method RECT has shown promising performance, its working mechanisms are not clear an…
Tempura: A General Cost Based Optimizer Framework for Incremental Data Processing (Extended Version)
Zuozhi Wang, Kai Zeng, Botong Huang +10
Incremental processing is widely-adopted in many applications, ranging from incremental view maintenance, stream computing, to recently emerging progressive data warehouse and inte…
Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks
Boyuan Feng, Yuke Wang, Zheng Wang +1
With the increasing popularity of graph-based learning, graph neural networks (GNNs) emerge as the essential tool for gaining insights from graphs. However, unlike the conventional…
BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning
Xinyue Chen, Zijian Zhou, Zheng Wang +3
There has recently been a surge in research in batch Deep Reinforcement Learning (DRL), which aims for learning a high-performing policy from a given dataset without additional int…