4 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 2 cited
HomoGCL: Rethinking Homophily in Graph Contrastive Learning
Wen-Zhi Li, Chang-Dong Wang, Hui Xiong +1
Contrastive learning (CL) has become the de-facto learning paradigm in self-supervised learning on graphs, which generally follows the "augmenting-contrasting" learning scheme. How…
cs.LG2023★ 4 cited
GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification
Wen-Zhi Li, Chang-Dong Wang, Hui Xiong +1
Class imbalance is the phenomenon that some classes have much fewer instances than others, which is ubiquitous in real-world graph-structured scenarios. Recent studies find that of…
cs.LG2023
One-step Bipartite Graph Cut: A Normalized Formulation and Its Application to Scalable Subspace Clustering
Si-Guo Fang, Dong Huang, Chang-Dong Wang +1
The bipartite graph structure has shown its promising ability in facilitating the subspace clustering and spectral clustering algorithms for large-scale datasets. To avoid the post…