305 citations · 575 across the 15 of their papers we have counts for
20 papers
High-order Multi-view Clustering for Generic Data
Erlin Pan, Zhao Kang
Graph-based multi-view clustering has achieved better performance than most non-graph approaches. However, in many real-world scenarios, the graph structure of data is not given or…
Scalable Multi-view Clustering with Graph Filtering
Liang Liu, Peng Chen, Guangchun Luo +3
With the explosive growth of multi-source data, multi-view clustering has attracted great attention in recent years. Most existing multi-view methods operate in raw feature space a…
Multi-view Contrastive Graph Clustering
Erlin Pan, Zhao Kang
With the explosive growth of information technology, multi-view graph data have become increasingly prevalent and valuable. Most existing multi-view clustering techniques either fo…
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-…
Smoothed Multi-View Subspace Clustering
Peng Chen, Liang Liu, Zhengrui Ma +1
In recent years, multi-view subspace clustering has achieved impressive performance due to the exploitation of complementary imformation across multiple views. However, multi-view…
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…