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An Online Expectation-Maximisation Algorithm for Nonnegative Matrix Factorisation Models

Machine Learning 2014-01-14 v1 Computation Machine Learning

Abstract

In this paper we formulate the nonnegative matrix factorisation (NMF) problem as a maximum likelihood estimation problem for hidden Markov models and propose online expectation-maximisation (EM) algorithms to estimate the NMF and the other unknown static parameters. We also propose a sequential Monte Carlo approximation of our online EM algorithm. We show the performance of the proposed method with two numerical examples.

Keywords

Cite

@article{arxiv.1401.2490,
  title  = {An Online Expectation-Maximisation Algorithm for Nonnegative Matrix Factorisation Models},
  author = {Sinan Yildirim and A. Taylan Cemgil and Sumeetpal S. Singh},
  journal= {arXiv preprint arXiv:1401.2490},
  year   = {2014}
}

Comments

6 pages, 3 figures

R2 v1 2026-06-22T02:43:14.798Z