Belief propagation for graph partitioning
Disordered Systems and Neural Networks
2010-06-16 v1 Statistical Mechanics
Discrete Mathematics
Data Structures and Algorithms
Abstract
We study the belief propagation algorithm for the graph bi-partitioning problem, i.e. the ground state of the ferromagnetic Ising model at a fixed magnetization. Application of a message passing scheme to a model with a fixed global parameter is not banal and we show that the magnetization can in fact be fixed in a local way within the belief propagation equations. Our method provides the full phase diagram of the bi-partitioning problem on random graphs, as well as an efficient heuristic solver that we anticipate to be useful in a wide range of application of the partitioning problem.
Keywords
Cite
@article{arxiv.0912.3563,
title = {Belief propagation for graph partitioning},
author = {P. Sulc and L. Zdeborova},
journal= {arXiv preprint arXiv:0912.3563},
year = {2010}
}
Comments
16 pages, 4 figures