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On the Partition Function and Random Maximum A-Posteriori Perturbations
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1206.6410.pdf
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Accepted version
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420.01 KB
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Adobe PDF
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Author(s) •
Hazan, Tamir
Jaakkola, Tommi
Date Issued
2012
Citation
Hazan, Tamir and Jaakkola, Tommi. 2012. "On the Partition Function and Random Maximum A-Posteriori Perturbations."
Version
Author's final manuscript
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. Copyright 2012 by the author(s)/owner(s).
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://icml.cc/2012/papers.1.html