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Deep belief networks are exact

Smirnov, Gleb
arXiv (All) · Papers
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artificial-intelligencemachine-learningprobability
We prove that every strictly positive probability distribution on \(\{-1,1\}^n\) is represented exactly by a sigmoid belief network with finite parameters. This answers a question of Sutskever and Hinton. The proof upgrades their probability-sharing approximation to exact representation using Brouwe
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