8 citations · 16 across the 5 of their papers we have counts for
4 papers · 1 filter
Cooperation of Experts: Fusing Heterogeneous Information with Large Margin
Shuo Wang, Shunyang Huang, Jinghui Yuan +2
Fusing heterogeneous information remains a persistent challenge in modern data analysis. While significant progress has been made, existing approaches often fail to account for the…
Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning
Zhixiang Shen, Shuo Wang, Zhao Kang
Unsupervised Multiplex Graph Learning (UMGL) aims to learn node representations on various edge types without manual labeling. However, existing research overlooks a key factor: th…
When Heterophily Meets Heterogeneous Graphs: Latent Graphs Guided Unsupervised Representation Learning
Zhixiang Shen, Zhao Kang
Unsupervised heterogeneous graph representation learning (UHGRL) has gained increasing attention due to its significance in handling practical graphs without labels. However, heter…
Balanced Multi-Relational Graph Clustering
Zhixiang Shen, Haolan He, Zhao Kang
Multi-relational graph clustering has demonstrated remarkable success in uncovering underlying patterns in complex networks. Representative methods manage to align different views…