Self-Paced Multi-View Clustering via a Novel Soft Weighted Regularizer

Multi-view clustering (MVC), which can exploit complementary information of different views to enhance the clustering performance, has attracted people's increasing attentions in recent years. However, existing multi-view clustering methods typically solve a non-convex problem, therefore are ea...

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Veröffentlicht in:	IEEE access 2019, Vol.7, p.168629-168636
Hauptverfasser:	Huang, Zongmo, Ren, Yazhou, Liu, Wenli, Pu, Xiaorong
Format:	Artikel
Sprache:	eng
Schlagworte:	Clustering Clustering algorithms Clustering methods Complexity theory Linear programming Multi-view clustering Noise measurement Optimization Outliers (statistics) self-paced learning soft weighting Training
Online-Zugang:	Volltext
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