Variational Inference for Stick-Breaking Beta Process Priors
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.
Cite
Text
Paisley et al. "Variational Inference for Stick-Breaking Beta Process Priors." International Conference on Machine Learning, 2011.Markdown
[Paisley et al. "Variational Inference for Stick-Breaking Beta Process Priors." International Conference on Machine Learning, 2011.](https://mlanthology.org/icml/2011/paisley2011icml-variational/)BibTeX
@inproceedings{paisley2011icml-variational,
title = {{Variational Inference for Stick-Breaking Beta Process Priors}},
author = {Paisley, John W. and Carin, Lawrence and Blei, David M.},
booktitle = {International Conference on Machine Learning},
year = {2011},
pages = {889-896},
url = {https://mlanthology.org/icml/2011/paisley2011icml-variational/}
}