332 citations · 393 across the 5 of their papers we have counts for
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Self-Supervised Graph Embedding Clustering
Fangfang Li, Quanxue Gao, Cheng Deng +1
The K-means one-step dimensionality reduction clustering method has made some progress in addressing the curse of dimensionality in clustering tasks. However, it combines the K-mea…
Rethinking k-means from manifold learning perspective
Quanxue Gao, Qianqian Wang, Han Lu +2
Although numerous clustering algorithms have been developed, many existing methods still leverage k-means technique to detect clusters of data points. However, the performance of k…
Multi-View Clustering via Semi-non-negative Tensor Factorization
Jing Li, Quanxue Gao, Qianqian Wang +2
Multi-view clustering (MVC) based on non-negative matrix factorization (NMF) and its variants have received a huge amount of attention in recent years due to their advantages in cl…
Self-supervised Contrastive Attributed Graph Clustering
Wei Xia, Quanxue Gao, Ming Yang +1
Attributed graph clustering, which learns node representation from node attribute and topological graph for clustering, is a fundamental but challenging task for graph analysis. Re…
Effective and Efficient Graph Learning for Multi-view Clustering
Quanxue Gao, Wei Xia, Xinbo Gao +3
Despite the impressive clustering performance and efficiency in characterizing both the relationship between data and cluster structure, existing graph-based multi-view clustering…