## Abstract

We present a variational Bayesian inference algorithm for the stick-breaking construction of the beta process. We derive an alternate representation of the beta process that is amenable to variational inference, and present a bound relating the truncated beta process to its infinite counterpart. We assess performance on two matrix factorization problems, using a non-negative factorization model and a linear-Gaussian model. Copyright 2011 by the author(s)/owner(s).

Original language | English (US) |
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Title of host publication | Proceedings of the 28th International Conference on Machine Learning, ICML 2011 |

Pages | 889-896 |

Number of pages | 8 |

State | Published - Oct 7 2011 |

Externally published | Yes |