Learning a Subspace and Clustering Simultaneously with Manifold Regularized Nonnegative Matrix Factorization

With the incredible growth of high-dimensional data such as microarray gene expression data and web blogs from internet, the researchers are desirable to develop new clustering techniques to address the critical problem created by irrelevant dimensions. Properties of Nonnegative Matrix Factorization...

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Autors principals:	Feiping Nie, Huimin Chen, Heng Huang, Chris H. Q. Ding, Xuelong Li
Format:	Artigo
Idioma:	Inglês
Publicat:	World Scientific Publishing Co Pte Ltd 2024-08-01
Col·lecció:	Guidance, Navigation and Control
Matèries:	Subspace learning clustering nonnegative matrix factorization manifold learning
Accés en línia:	https://www.worldscientific.com/doi/10.1142/S2737480724500134
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