49 citations · 70 across the 7 of their papers we have counts for
4 papers · 1 filter
Self-supervised Consensus Representation Learning for Attributed Graph
Changshu Liu, Liangjian Wen, Zhao Kang +2
Attempting to fully exploit the rich information of topological structure and node features for attributed graph, we introduce self-supervised learning mechanism to graph represent…
Self-paced Principal Component Analysis
Zhao Kang, Hongfei Liu, Jiangxin Li +2
Principal Component Analysis (PCA) has been widely used for dimensionality reduction and feature extraction. Robust PCA (RPCA), under different robust distance metrics, such as l1-…
Towards Clustering-friendly Representations: Subspace Clustering via Graph Filtering
Zhengrui Ma, Zhao Kang, Guangchun Luo +1
Finding a suitable data representation for a specific task has been shown to be crucial in many applications. The success of subspace clustering depends on the assumption that the…
Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages
Yi Luo, Aiguo Chen, Ke Yan +1
Nowadays, Graph Neural Networks (GNNs) following the Message Passing paradigm become the dominant way to learn on graphic data. Models in this paradigm have to spend extra space to…