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arXiv · 1206.6410

On the Partition Function and Random Maximum A-Posteriori Perturbations

Tamir Hazan·Tommi Jaakkola
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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.

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Tamir Hazan, Tommi Jaakkola. 2012-06-27. On the Partition Function and Random Maximum A-Posteriori Perturbations. https://arxiv.org/abs/1206.6410

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