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|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.|
|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).|
|Type of Material:||Conference Article|
|Journal/Proceeding Title:||Proceedings of the 28th International Conference on Machine Learning|
|Version:||Final published version. Article is made available in OAR by the publisher's permission or policy.|
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