Graphical Models and Inference - 2012

Organizer: Nicholas Ruozzi
Office: INR 136
Phone: 37551
Email: nicholas.ruozzi@epfl.ch

Meetings: Fridays 4:15pm - 5:30pm in room INR 113

The objective of the reading group is to understand the recent results in the study of graphical models and approximate inference. No background in graphical models or message passing is required.

A tentative list of topics includes:

• Factor graphs and message passing as dynamic programming on a tree
• Message passing (belief propagation, max-product, min-sum): admissibility, consistency, and computation trees
• Message passing for the maximum weight matching problem
• Message passing for optimization: MAP LP and reparameterizations
• Graph covers and pseudocodewords
• Convergent and correct message passing: TRMP, MPLP, etc.
• Variational approximations and belief propagation
• Variational approximations: zero temperature limits of BP and generalized belief propagation
• Convex entropy approximations and convergent message passing: TRBP and others
• Graph covers and the Bethe partition function
• Loop Expansions

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