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Poster
Non-conjugate Variational Message Passing for Multinomial and Binary Regression
David A Knowles · Tom Minka

Mon Dec 12 10:00 AM -- 02:59 PM (PST) @
in Poster Session and Reception »

Variational Message Passing (VMP) is an algorithmic implementation of the Variational Bayes (VB) method which applies only in the special case of conjugate exponential family models. We propose an extension to VMP, which we refer to as Non-conjugate Variational Message Passing (NCVMP) which aims to alleviate this restriction while maintaining modularity, allowing choice in how expectations are calculated, and integrating into an existing message-passing framework: Infer.NET. We demonstrate NCVMP on logistic binary and multinomial regression. In the multinomial case we introduce a novel variational bound for the softmax factor which is tighter than other commonly used bounds whilst maintaining computational tractability.

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Author Information

David A Knowles (Stanford University)
Tom Minka (MSR)

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