A Majorization-Minimization Algorithm for Nonnegative Binary Matrix Factorization

This paper tackles the problem of decomposing binary data using matrix factorization. We consider the family of mean-parametrized Bernoulli models, a class of generative models that are well suited for modeling binary data and enables interpretability of the factors. We factorize the Bernoulli param...

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Veröffentlicht in:	IEEE signal processing letters Jg. 29; S. 1526 - 1530
Hauptverfasser:	Magron, Paul, Fevotte, Cedric
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.01.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Schlagworte:	Algorithms Bayesian analysis Binary data Biological system modeling Computational modeling Computer Science Data models Estimation Factorization Information Retrieval Logistics majorization-minimization Mathematical models mean-parametrized Bernoulli model nonnegative matrix factorization Optimization Parameters Performance enhancement Principal component analysis Statistical inference Upper bound binary data mean-parametrized Bernoulli model majorization-minimization nonnegative matrix factorization
ISSN:	1070-9908, 1558-2361
Online-Zugang:	Volltext
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