A Spectral Approach to Analyzing Belief Propagation for 3-Coloring
arXiv:0712.0171 · doi:10.1017/S096354830900981X
Abstract
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 coloring 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 possible permutations of the color classes.
References in corpus (1)
Cited by in corpus (9)
- Influence maximization in complex networks through optimal percolation
- Spectral redemption: clustering sparse networks
- Statistical physics of inference: Thresholds and algorithms
- Quiet Planting in the Locked Constraint Satisfaction Problems
- Spectral Detection on Sparse Hypergraphs
- On belief propagation guided decimation for random k-SAT
- Decoding from Pooled Data: Sharp Information-Theoretic Bounds
- Spectral partitioning in equitable graphs
- The solution space structure of planted constraint satisfaction problems with growing domains