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Boltzmann machine / Cybernetics / Neuroscience / Connectionism / Geoffrey Hinton / Mathematical optimization / Types of artificial neural networks / Hopfield network / Neural networks / Computational neuroscience / Science


Document Date: 2009-01-08 17:51:01

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Facility

David Carnegie-Mellon University / /

IndustryTerm

large systems / minimum energy configuration / low energy / local energy minimum / possible solution / energy gap / parallel constraint satisfaction network / search technique / domain-independent learning algorithm / human information processing / primitive computing / higher energy / deterministic algorithm / energy states / local energy minima / nonlinear networks / thermodynamic systems / lower total energy / neuron-like processing elements / parallel networks / energy difference / conditions networks / energy differences / learning algorithm / fhe global energy / learning algorithms / energy / /

Organization

BOLTZMANN MACHINE The Boltzmann Machine / The Johns Hopkins University / Computer Science Department / David Carnegie-Mellon University / Pittsburgh / /

Person

Ackley / Jay Paul Smolensky / Jerry Barak Pearlmutter / GEOFFREY E. HINTON / TERRENCE J. SEJNOWSKI / Peter Brown / DAVID H. ACKLEY GEOFFREY / Rosenbluth / Stuart Geman / Francis Feldman / John Harry Printz / Mark Hopfield / Dave Rumelhart / Tim Shallice / Gail Gong / /

Position

Teller / /

ProvinceOrState

Pennsylvania / /

Technology

learning algorithm / VLSI technology / artificial intelligence / MACHINE LEARNING / Metroplis algorithm / /

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