79 citations · 132 across the 7 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2022
HybridGNN: Learning Hybrid Representation in Multiplex Heterogeneous Networks
Tiankai Gu, Chaokun Wang, Cheng Wu +6
Recently, graph neural networks have shown the superiority of modeling the complex topological structures in heterogeneous network-based recommender systems. Due to the diverse int…
cs.LG2021★ 1 cited
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…
cs.LG2020★ 52 cited
Network Embedding with Completely-imbalanced Labels
Zheng Wang, Xiaojun Ye, Chaokun Wang +2
Network embedding, aiming to project a network into a low-dimensional space, is increasingly becoming a focus of network research. Semi-supervised network embedding takes advantage…