Variational inference in graphical models: The view from the marginal polytope

Add to your list(s) Download to your calendar using vCal

• David Knowles and Richard Turner (University of Cambridge)
• Thursday 04 February 2010, 14:00-15:30
• Engineering Department, CBL Room 438.

If you have a question about this talk, please contact Shakir Mohamed.

In last week’s RCC , we saw that loopy belief propagation could be connected to a constrained variational free energy optimisation. The constraints ensured that the beliefs normalised and that they were locally consistent. This week, we’ll describe an alternate view of this optimisation which separately considers the constraints (the domain being called the marginal polytope) and the free-energy. The optimization takes place over the lower dimensional space of generalised exponential family mean parameters. This representation clarifies that there are two distinct components to variational inference algorithms: (a) an approximation to the entropy function; and (b) an approximation to the marginal polytope. This viewpoint clarifies the essential ingredients of known variational methods, and also suggests novel relaxations. Taking the “zero-temperature limit” recovers a variational representation for MAP computation as a linear program (LP) over the marginal polytope.

The material we hope to cover (and probably some extra) is covered on slides 1-13 and 23-39 of this tutorial

If you feel inclined to delve into the theory a little more, refer to this paper

This talk is part of the Machine Learning Reading Group @ CUED series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge University Engineering Department Talks
• Cambridge talks
• Centre for Smart Infrastructure & Construction
• Chris Davis' list
• Engineering Department, CBL Room 438
• Featured lists
• Guy Emerson's list
• Hanchen DaDaDash
• Inference Group Journal Clubs
• Inference Group Summary
• Information Engineering Division seminar list
• Interested Talks
• ML
• Machine Learning Reading Group
• Machine Learning Reading Group @ CUED
• Machine Learning Summary
• Quantum Matter Journal Club
• Required lists for MLG
• School of Technology
• Simon Baker's List
• TQS Journal Clubs
• Trust & Technology Initiative - interesting events
• bld31
• custom
• ndk22's list
• rp587
• yk373's list

Note that ex-directory lists are not shown.