Variational inference for stick-breaking beta process priors

John Paisley, Lawrence Carin, David Blei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

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 languageEnglish (US)
Title of host publicationProceedings of the 28th International Conference on Machine Learning, ICML 2011
Pages889-896
Number of pages8
StatePublished - Oct 7 2011
Externally publishedYes

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