Multi-layer manifold learning for deep non-negative matrix factorization-based multi-view clustering

•An orthogonal deep non-negative matrix factorization (Deep-NMF) framework that aims to learn the non-linear parts-based representation for multi-view data is proposed.•The T-SNE visualizations of the features learned by the proposed Deep-NMF and its counterpart ascertain the effectiveness of the pr...

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Veröffentlicht in:	Pattern recognition Jg. 131; S. 108815
Hauptverfasser:	Luong, Khanh, Nayak, Richi, Balasubramaniam, Thirunavukarasu, Bashar, Md Abul
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.11.2022
Schlagworte:	Deep Matrix Factorization (DMF) Deep Non-negative Matrix Factorization (Deep-NMF) Manifold learning Multi-view data/clustering Non-negative Matrix Factorization (NMF) Multi-view data/clustering Manifold learning Deep Non-negative Matrix Factorization (Deep-NMF) Non-negative Matrix Factorization (NMF) Deep Matrix Factorization (DMF)
ISSN:	0031-3203, 1873-5142
Online-Zugang:	Volltext
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