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Gibbs Measures and Phase Transitions on Sparse Random Graphs

Author: Amir Dembo, Andrea Montanari
Url: http://arxiv.org/abs/0910.5460
Format: Ps,Pdf
Year: 2009
Category: Graph Theory, Probability Theory
Pages: 111
Clicks: 2460

Many problems of interest in computer science and information theory can be phrased in terms of a probability distribution over discrete variables associated to the vertices of a large (but finite) sparse graph. In recent years, considerable progress has been achieved by viewing these distributions as Gibbs measures and applying to their study heuristic tools from statistical physics. We review this approach and provide some results towards a rigorous treatment of these problems.

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