A class of random fields on complete graphs with tractable partition function
Machine Learning
2013-06-19 v2 Machine Learning
Abstract
The aim of this short note is to draw attention to a method by which the partition function and marginal probabilities for a certain class of random fields on complete graphs can be computed in polynomial time. This class includes Ising models with homogeneous pairwise potentials but arbitrary (inhomogeneous) unary potentials. Similarly, the partition function and marginal probabilities can be computed in polynomial time for random fields on complete bipartite graphs, provided they have homogeneous pairwise potentials. We expect that these tractable classes of large scale random fields can be very useful for the evaluation of approximation algorithms by providing exact error estimates.
Cite
@article{arxiv.1212.2136,
title = {A class of random fields on complete graphs with tractable partition function},
author = {Boris Flach},
journal= {arXiv preprint arXiv:1212.2136},
year = {2013}
}
Comments
accepted for publication in IEEE TPAMI (short paper)