An introduction to Bayesian inference (with an application to network analysis)

Jan 13, 2010 · New York, United States of America

Jake Hofman from Yahoo! Research will give an introduction to Bayesian inference, including a discussion of the Bayesian interpretation of probability. After a review of the underlying theory, he'll discuss the practical aspects of Bayesian inference for real-world problems. Jake will conclude with an example of his own research in applying variational Bayesian methods to the problem of community detection in networks. The following are a few relevant references for the talk. First, a reading list for Bayesian methods from Tom Griffiths at UC Berkeley: In particular, this tutorial may be of interest: http://cocosci.berkel... David MacKay's book (free pdf online) on information theory has several relevant chapters, including Chapter 2 for a review of probability theory and Bayesian inference, and Section IV for an in-depth discussion of subtopics: http://www.inference.... Finally, the following are links to software and papers for the work Jake will discuss on Bayesian inference for community detection in networks: http://vbmod.sourcefo... Please note that we've changed locations again. Gilt Groupe is still our awesome host, but this time in their new office.

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