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A Better Way to Pretrain Deep Boltzmann Machines Geoffrey Hinton Department of Computer Science University of Toronto [removed]
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Document Date: 2012-12-30 16:52:13

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Company

Deep Belief Networks / Neural Information Processing Systems / Google / Microsoft / /

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Facility

Computer Science University / Canadian Institute / In Ph.D. New York University / /

IndustryTerm

layer-wise pretraining algorithm / stochastic approximation algorithm / directed sigmoid belief network / belief networks / pretraining algorithm / stochastic algorithms / meanfield algorithm / learning algorithm / /

Organization

New York University / Department of Statistics / U.S. Securities and Exchange Commission / Pretrain Deep Boltzmann Machines Geoffrey Hinton Department / University of Toronto / Canadian Institute for Advanced Research / /

Person

Ruslan Salakhutdinov / /

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Product

4W / /

PublishedMedium

Machine Learning / Journal of Machine Learning Research / Lecture Notes in Computer Science / /

Technology

artificial intelligence / existing pretraining algorithms / 6 Algorithm / pretraining algorithm / stochastic approximation algorithm / Machine Learning / pretraining algorithms / second algorithm / meanfield algorithm / DBMs / 3.1 Pretraining Algorithm / 1 Greedy Pretraining Algorithm / existing pretraining algorithm / layer-wise pretraining algorithm / /

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