Orthogonal nonnegative matrix factorization problems for clustering: A new formulation and a competitive algorithm

Orthogonal Nonnegative Matrix Factorization (ONMF) with orthogonality constraints on a matrix has been found to provide better clustering results over existing clustering problems. Because of the orthogonality constraint, this optimization problem is difficult to solve. Many of the existing constrai...

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Veröffentlicht in:	Annals of operations research Jg. 339; H. 3; S. 1481 - 1497
Hauptverfasser:	Dehghanpour, Ja’far, Mahdavi-Amiri, Nezam
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.08.2024 Springer
Schlagworte:	Algorithms Business and Management Clustering (Computers) Combinatorics Data mining Mathematical optimization Operations Research/Decision Theory Original Research Theory of Computation Iran Isoperimetry problem Clustering Optimization problem with orthogonality constraints Orthogonal Nonnegative Matrix Factorization
ISSN:	0254-5330, 1572-9338
Online-Zugang:	Volltext
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