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A Bayesian Approach to the Lee-Seung Update Rules for NMF

Authors
Journal
Pattern Recognition Letters
0167-8655
Publisher
Elsevier
Volume
45
Identifiers
DOI: 10.1016/j.patrec.2014.04.013
Keywords
  • Variational Bayes Nmf
  • Bayesian Optimality Criteria
  • Lee-Seung Update Rules
Disciplines
  • Computer Science

Abstract

Abstract NMF is a Blind Source Separation technique decomposing multivariate non-negative data sets into meaningful non-negative basis components and non-negative weights. In its canonical form an NMF algorithm was proposed by Lee and Seung [31] employing multiplicative update rules. In this study we show how the latter follow from a new variational Bayes NMF algorithm VBNMF employing a Gaussian noise kernel.

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