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A Novel Tree Block-Coordinate Method for MAP Inference

  • Christopher Zach
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9358)

Abstract

Block-coordinate methods inspired by belief propagation are among the most successful methods for approximate MAP inference in graphical models. The set of unknowns optimally updated in such block-coordinate methods is typically very small and spans only single edges or shallow trees. We derive a method that optimally updates sets of unknowns spanned by an arbitrary tree that is different from one reported in the literature. It provides some insight why “tree block-coordinate” methods are not as useful as expected, and enables a simple technique to makes these tree updates more effective.

Supplementary material

371393_1_En_26_MOESM1_ESM.zip (678 kb)
Supplementary material 1 (zip 678 KB)

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Copyright information

© Springer International Publishing Switzerland 2015

Open Access This chapter is distributed under the terms of the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Authors and Affiliations

  1. 1.Toshiba Research EuropeCambridgeUK

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