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arXiv · 1312.6205

Relaxations for inference in restricted Boltzmann machines

Sida I. Wang·Roy Frostig·Percy Liang·Christopher D. Manning
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Abstract

We propose a relaxation-based approximate inference algorithm that samples near-MAP configurations of a binary pairwise Markov random field. We experiment on MAP inference tasks in several restricted Boltzmann machines. We also use our underlying sampler to estimate the log-partition function of restricted Boltzmann machines and compare against other sampling-based methods.

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Sida I. Wang, Roy Frostig, Percy Liang, Christopher D. Manning. 2014-01-02. Relaxations for inference in restricted Boltzmann machines. https://arxiv.org/abs/1312.6205

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