Efficient Multi-View Clustering via Unified and Discrete Bipartite Graph Learning

Although previous graph-based multi-view clustering (MVC) algorithms have gained significant progress, most of them are still faced with three limitations. First, they often suffer from high computational complexity, which restricts their applications in large-scale scenarios. Second, they usually p...

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Vydané v:	IEEE transaction on neural networks and learning systems Ročník 35; číslo 8; s. 11436 - 11447
Hlavní autori:	Fang, Si-Guo, Huang, Dong, Cai, Xiao-Sha, Wang, Chang-Dong, He, Chaobo, Tang, Yong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.08.2024
Predmet:	Bipartite graph Bipartite graph learning Clustering algorithms data clustering Fuses Laplace equations large-scale clustering Linear programming linear time multi-view clustering (MVC) Optimization Partitioning algorithms
ISSN:	2162-237X, 2162-2388, 2162-2388
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