Fast Bayesian Non-Negative Matrix Factorisation and Tri-Factorisation

Thomas Brouwer; Jes Frellsen; Pietro Lio'

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arXiv · 1610.08127

Fast Bayesian Non-Negative Matrix Factorisation and Tri-Factorisation

Thomas Brouwer·Jes Frellsen·Pietro Lio'

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Abstract

We present a fast variational Bayesian algorithm for performing non-negative matrix factorisation and tri-factorisation. We show that our approach achieves faster convergence per iteration and timestep (wall-clock) than Gibbs sampling and non-probabilistic approaches, and do not require additional samples to estimate the posterior. We show that in particular for matrix tri-factorisation convergence is difficult, but our variational Bayesian approach offers a fast solution, allowing the tri-factorisation approach to be used more effectively.

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Thomas Brouwer, Jes Frellsen, Pietro Lio'. 2016-10-26. Fast Bayesian Non-Negative Matrix Factorisation and Tri-Factorisation. https://arxiv.org/abs/1610.08127

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