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Algorithms for non-negative matrix factorization

D Seung, +1 more
- Vol. 13, pp 556-562
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The article was published on 2001-01-01 and is currently open access. It has received 5015 citations till now. The article focuses on the topics: Non-negative matrix factorization.

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Journal ArticleDOI

A framework for regularized non-negative matrix factorization, with application to the analysis of gene expression data.

TL;DR: Novel methods for regularized NMF based on block-coordinate descent with proximal point modification and a fast optimization procedure over the alpha simplex are developed and illustrated in the context of gene expression microarray data analysis.
Journal ArticleDOI

Subtractive clustering for seeding non-negative matrix factorizations

TL;DR: The adoption of the subtractive clustering algorithm is proposed as a scheme to generate initial matrices for non-negative matrix factorization algorithms and the proposed scheme reveals to be a good trade-off between effectiveness and speed.
Journal ArticleDOI

EMG-Centered Multisensory Based Technologies for Pattern Recognition in Rehabilitation: State of the Art and Challenges.

TL;DR: The principle of EMG signal generation and the current pattern recognition process are explained in detail, including signal preprocessing, feature extraction, classification algorithms, etc, and Mechanisms of collaborations between two important multisensory fusion strategies and EMG information are thoroughly explained.
Book ChapterDOI

Orthogonal Nonnegative Matrix Factorization: Multiplicative Updates on Stiefel Manifolds

TL;DR: In this article, an orthogonality constraint is imposed on the nonnegative decomposition of a term-document matrix, and the authors develop multiplicative updates directly from true gradient on Stiefel manifold.
Journal ArticleDOI

Piecewise Convex Multiple-Model Endmember Detection and Spectral Unmixing

TL;DR: The results indicate that the piecewise convex representation estimates endmembers that better represent hyperspectral imagery composed of multiple regions where each region is represented with a distinct set of endmembers.
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