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Science / Neural network / Pattern recognition / Supervised learning / Caltech 101 / Unsupervised learning / Machine learning / Artificial intelligence / Learning


Document Date: 2012-07-12 20:39:43

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City

Courville / Edinburgh / /

Company

Cox D. D. / LG / YouTube / Weston / /

Country

United Kingdom / Scotland / /

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Facility

University of Montreal / University of Toronto / University of Massachusetts / E. Building / /

IndustryTerm

software framework / overall network / feature learning algorithms / autoencoders network / sparse coding algorithms / neural networks / large networks / singlelayer networks / line search / temporal product network / deep learning algorithms / unsupervised learning using graphics processors / deep belief networks / convolutional neural networks / recent successful algorithms / algorithms / learning algorithm / Experimental protocols / learning algorithms / /

MarketIndex

set 10 / /

Organization

University of Massachusetts / Amherst / University of Montreal / University of Toronto / /

Person

Devin Kai Chen Greg / Aurelio Ranzato Rajat Monga Matthieu / Jon Shlens / Mark Mao / Adam Coates / Rajat Monga Matthieu Devin Kai / Dean Andrew / Matthieu Devin Kai Chen / Peter Norvig / Jia Deng / Greg S. Corrado Je / Andrew Saxe / Paul Tucker / Tom Dean / /

Position

author / model / and the computational resources / deep belief net model for visual area V2 / /

ProvinceOrState

Massachusetts / /

PublishedMedium

Machine Learning / PLoS Computational Biology / The Journal of Neuroscience / Nature Neuroscience / /

Technology

Neuroscience / deep unsupervised learning using graphics processors / Machine Learning / deep learning algorithms / same experimental protocols / feature learning algorithms / sparse coding algorithms / neural network / artificial intelligence / Architecture Our algorithm / /

URL

http /

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