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...

Full description

Bibliographic Details

Published in:	Annals of operations research Vol. 339; no. 3; pp. 1481 - 1497
Main Authors:	Dehghanpour, Ja’far, Mahdavi-Amiri, Nezam
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.08.2024 Springer
Subjects:	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 Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!