Schachtner, R. and Poeppel, G. and Tome, A. M. and Lang, W. (2014) A Bayesian approach to the Lee-Seung update rules for NMF. PATTERN RECOGNITION LETTERS, 45. pp. 251-256. ISSN 0167-8655, 1872-7344
Full text not available from this repository. (Request a copy)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 (1999) [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. (C) 2014 Elsevier B.V. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | NONNEGATIVE MATRIX FACTORIZATION; INDEPENDENT COMPONENT ANALYSIS; ALGORITHMS; CLASSIFICATION; MODELS; PCA; Variational Bayes NMF; Bayesian optimality criteria; Lee-Seung update rules |
| Subjects: | 500 Science > 570 Life sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 30 Sep 2019 13:53 |
| Last Modified: | 30 Sep 2019 13:53 |
| URI: | https://pred.uni-regensburg.de/id/eprint/9858 |
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