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Multi-view nonnegative matrix factorization via orthogonal and adversarial graph regularization

delete2025-07-03
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PRE
AI
N
Ning Li
C
Chengcai Leng
J
Jinye Peng
I
Irene Cheng
A
Anup Basu
L
Licheng Jiao
DOI：10.1016/j.asoc.2025.113508delete
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Abstract

Abstract

En 中文
• A novel multi-view NMF method called OAGNMF is proposed. • We consider sample information from different and same categories of data. • The feasible set of the Laplace matrix is enlarged. • We prove the superior clustering performance of OAGNMF.

Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
Papers:
1.4W
Citations:
4.8W

Organization

No organization information available