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Applied mathematics / Backpropagation / Almeida–Pineda recurrent backpropagation / GeneRec / Boltzmann machine / Activation function / Autoencoder / Leabra / Algorithm / Neural networks / Cybernetics / Science


Document Date: 1999-01-19 20:24:12

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Company

BP / /

Country

Jordan / /

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Event

Product Issues / /

Facility

Psychology Carnegie Mellon University / /

IndustryTerm

energy function / layer network / fixed point solutions / error backpropagation learning algorithm / deterministic networks / connected networks / generic recurrent network / auto-encoder networks / recurrent networks / layer backprop network / generalized recirculation algorithm / recirculation algorithm / deterministic recurrent networks / error-driven learning algorithms / recurrent network / recurrent backpropagation algorithm / feedforward backprop network / sigmoidal recurrent network / backpropagation algorithm / earlier algorithm / connected network / fixed point solution / stochastic networks / learning algorithm / learning algorithms / energy / contrastiveHebbian learning algorithm / /

Organization

Generalized Recirculation Algorithm Randall C. O’Reilly Department of Psychology Carnegie Mellon University Pittsburgh / US Federal Reserve / /

Person

Almeida-Pineda Recurrent / /

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Position

author / /

Product

approximation / /

ProvinceOrState

Pennsylvania / /

Technology

earlier algorithm / AP recurrent backpropagation algorithm / contrastive-Hebbian learning algorithm / generalized recirculation algorithm / error backpropagation learning algorithm / GeneRec algorithm / CHL algorithm / error-driven learning algorithms / AP algorithm / 1996 Abstract The error backpropagation learning algorithm / CHL algorithms / AP algorithms / simulation / contrastiveHebbian learning algorithm / backpropagation algorithm / recirculation algorithm / deterministic CHL algorithm / /

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