Variational Inference for Stick-Breaking Beta Process Priors

Author(s): Paisley, John; Carin, Lawrence; Blei, David

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DC Field	Value	Language
dc.contributor.author	Paisley, John	-
dc.contributor.author	Carin, Lawrence	-
dc.contributor.author	Blei, David	-
dc.date.accessioned	2021-10-08T19:50:20Z	-
dc.date.available	2021-10-08T19:50:20Z	-
dc.date.issued	2011	en_US
dc.identifier.citation	Paisley, John, Lawrence Carin, and David Blei. "Variational Inference for Stick-Breaking Beta Process Priors." Proceedings of the 28th International Conference on Machine Learning (2011).	en_US
dc.identifier.uri	https://icml.cc/2011/papers/475_icmlpaper.pdf	-
dc.identifier.uri	http://arks.princeton.edu/ark:/88435/pr1wr9r	-
dc.description.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 linearGaussian model.	en_US
dc.language.iso	en_US	en_US
dc.relation.ispartof	Proceedings of the 28th International Conference on Machine Learning	en_US
dc.rights	Final published version. Article is made available in OAR by the publisher's permission or policy.	en_US
dc.title	Variational Inference for Stick-Breaking Beta Process Priors	en_US
dc.type	Conference Article	en_US
pu.type.symplectic	http://www.symplectic.co.uk/publications/atom-terms/1.0/conference-proceeding	en_US

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