Variational inference for stick-breaking beta process priors


Journal Article

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).

Duke Authors

Cited Authors

  • Paisley, J; Carin, L; Blei, D

Published Date

  • October 7, 2011

Published In

  • Proceedings of the 28th International Conference on Machine Learning, Icml 2011

Start / End Page

  • 889 - 896

Citation Source

  • Scopus