A Unifying Framework and Comparison of Algorithms for Non‐negative Matrix Factorisation

Summary Non‐negative matrix factorisation (NMF) is an increasingly popular unsupervised learning method. However, parameter estimation in the NMF model is a difficult high‐dimensional optimisation problem. We consider algorithms of the alternating least squares type. Solutions to the least squares p...

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Veröffentlicht in:	International statistical review 2020-04, Vol.88 (1), p.29-53
Hauptverfasser:	Hobolth, Asger, Guo, Qianyun, Kousholt, Astrid, Jensen, Jens Ledet
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Cancer Cone projection EM‐algorithm Factorization Iterative algorithms Iterative methods Least squares method mutational signatures non‐negative least squares (NLS) non‐negative matrix factorisation (NMF) Optimization Parameter estimation Projection
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