2000 character limit reached
On the Partition Function and Random Maximum A-Posteriori Perturbations (1206.6410v1)
Published 27 Jun 2012 in cs.LG and stat.ML
Abstract: In this paper we relate the partition function to the max-statistics of random variables. In particular, we provide a novel framework for approximating and bounding the partition function using MAP inference on randomly perturbed models. As a result, we can use efficient MAP solvers such as graph-cuts to evaluate the corresponding partition function. We show that our method excels in the typical "high signal - high coupling" regime that results in ragged energy landscapes difficult for alternative approaches.