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Relaxations for inference in restricted Boltzmann machines.

International Conference on Learning Representations, (2013)

Cited: 7|Views60
EI

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...More

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