Local stability of Belief Propagation algorithm with multiple fixed points - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2012

Local stability of Belief Propagation algorithm with multiple fixed points

Abstract

A number of problems in statistical physics and computer science can be expressed as the computation of marginal probabilities over a Markov random field. Belief propagation, an iterative message-passing algorithm, computes exactly such marginals when the underlying graph is a tree. But it has gained its popularity as an efficient way to approximate them in the more general case, even if it can exhibits multiple fixed points and is not guaranteed to converge. In this paper, we express a new sufficient condition for local stability of a belief propagation fixed point in terms of the graph structure and the beliefs values at the fixed point. This gives credence to the usual understanding that Belief Propagation performs better on sparse graphs.
Fichier principal
Vignette du fichier
FreeSTAIRS.pdf (150.82 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00719204 , version 1 (26-07-2012)

Identifiers

  • HAL Id : hal-00719204 , version 1

Cite

Victorin Martin, Jean-Marc Lasgouttes, Cyril Furtlehner. Local stability of Belief Propagation algorithm with multiple fixed points. STAIRS'12 - Sixth "Starting Artificial Intelligence Research" Symposium, Aug 2012, Montpellier, France. pp.180-191. ⟨hal-00719204⟩
229 View
105 Download

Share

Gmail Facebook X LinkedIn More