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arxiv: 1703.00663 · v1 · pith:FEAGK52Tnew · submitted 2017-03-02 · 💻 cs.NA · cs.CV· cs.LG· math.OC· stat.ML

Introduction to Nonnegative Matrix Factorization

Nicolas Gillis This is my paper
classification 💻 cs.NA cs.CVcs.LGmath.OCstat.ML
keywords matrixfactorizationnonnegativealgorithmsapplicationapproximationaspectsbriefly
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In this paper, we introduce and provide a short overview of nonnegative matrix factorization (NMF). Several aspects of NMF are discussed, namely, the application in hyperspectral imaging, geometry and uniqueness of NMF solutions, complexity, algorithms, and its link with extended formulations of polyhedra. In order to put NMF into perspective, the more general problem class of constrained low-rank matrix approximation problems is first briefly introduced.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. An Exterior Method for Nonnegative Matrix Factorization

    cs.LG 2026-05 conditional novelty 7.0

    eNMF is a new exterior-point algorithm for NMF that initializes from unconstrained factorization, applies a rotation to reach the nonnegative boundary, and empirically outperforms 81 baseline combinations on real and ...