Statistics > Machine Learning
[Submitted on 19 Jul 2015 (v1), last revised 21 Jul 2015 (this version, v2)]
Title:The Population Posterior and Bayesian Inference on Streams
View PDFAbstract:Many modern data analysis problems involve inferences from streaming data. However, streaming data is not easily amenable to the standard probabilistic modeling approaches, which assume that we condition on finite data. We develop population variational Bayes, a new approach for using Bayesian modeling to analyze streams of data. It approximates a new type of distribution, the population posterior, which combines the notion of a population distribution of the data with Bayesian inference in a probabilistic model. We study our method with latent Dirichlet allocation and Dirichlet process mixtures on several large-scale data sets.
Submission history
From: James McInerney [view email][v1] Sun, 19 Jul 2015 07:19:22 UTC (1,152 KB)
[v2] Tue, 21 Jul 2015 20:41:38 UTC (1,152 KB)
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