Oct 19, 2012 · We present a class of generalized mean field (GMF) algorithms for approximate inference in complex exponential family models, which entails ...
A generalized mean field algorithm for variational inference in exponential families. Eric P. Xing. Computer Science Division. University of California.
We present a class of generalized mean field. (GMF) algorithms for approximate inference in exponential family graphical models which.
We present a class of generalized mean field (GMF) algorithms for approximate inference in complex exponential family models, which entails limiting the ...
Aug 7, 2002 · We present a ciass of generalized mean field (GMF) algorithms for approximate inference in exponential family graphical models which is ...
Aug 8, 2003 · Definition 1. (Mean field message) The expected sufficient statistics of variable(s) coupled with other variable(s) in the neighboring ...
A class of generalized mean field algorithms for approximate inference in complex exponential family models, which entails limiting the optimization over ...
'fie present a ciass of generaiizeci mean fieid. (GMF) algorithms for approximate inference in exponential family graphical models which.
Apr 2, 2021 · Writing this update in terms of variational parameters . ○ Give each latent variable a variational parameter . Under the mean field assumption, ...
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A generalized mean field algorithm for variational inference in exponential families. E. P. Xing, M. I. Jordan, and S. Russell. In C. Meek and U. Kjaerulff ...