Title
A spectral approach to analysing belief propagation for 3-colouring
Abstract
Belief propagation (BP) is a message-passing algorithm that computes the exact marginal distributions at every vertex of a graphical model without cycles. While BP is designed to work correctly on trees, it is routinely applied to general graphical models that may contain cycles, in which case neither convergence, nor correctness in the case of convergence is guaranteed. Nonetheless, BP has gained popularity as it seems to remain effective in many cases of interest, even when the underlying graph is ‘far’ from being a tree. However, the theoretical understanding of BP (and its new relative survey propagation) when applied to CSPs is poor. Contributing to the rigorous understanding of BP, in this paper we relate the convergence of BP to spectral properties of the graph. This encompasses a result for random graphs with a ‘planted’ solution; thus, we obtain the first rigorous result on BP for graph colouring in the case of a complex graphical structure (as opposed to trees). In particular, the analysis shows how belief propagation breaks the symmetry between the 3! possible permutations of the colour classes.
Year
DOI
Venue
2007
10.1017/S096354830900981X
Clinical Orthopaedics and Related Research
Keywords
DocType
Volume
random graph,rigorous result,rigorous understanding,spectral algorithms.,graph coloring,graphical model,survey propagation,theoretical understanding,belief propagation,complex graphical structure,spectral approach,underlying graph,analysing belief propagation,new relative survey propagation,general graphical model
Journal
18
Issue
ISSN
Citations 
6
0963-5483
10
PageRank 
References 
Authors
0.85
15
3
Name
Order
Citations
PageRank
Amin Coja-Oghlan154347.25
Elchanan Mossel21725145.16
Dan Vilenchik314313.36