Multiview Subspace Clustering by an Enhanced Tensor Nuclear Norm

Despite the promising preliminary results, tensor-singular value decomposition (t-SVD)-based multiview subspace is incapable of dealing with real problems, such as noise and illumination changes. The major reason is that tensor-nuclear norm minimization (TNNM) used in t-SVD regularizes each singular...

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Veröffentlicht in:	IEEE transactions on cybernetics Jg. 52; H. 9; S. 8962 - 8975
Hauptverfasser:	Xia, Wei, Zhang, Xiangdong, Gao, Quanxue, Shu, Xiaochuang, Han, Jungong, Gao, Xinbo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.09.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Clustering Clustering algorithms Clustering methods Coefficients Correlation Learning Mathematical analysis Matrix decomposition Minimization Multiview clustering Optimization Periodic structures Singular value decomposition spectral clustering Subspaces tensor-singular value decomposition (t-SVD) Tensors weighted nuclear norm
ISSN:	2168-2267, 2168-2275, 2168-2275
Online-Zugang:	Volltext
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