Deep unsupervised learning on a desktop PC: A primer for cognitive scientists

Deep unsupervised learning on a desktop PC: A primer for cognitive scientists

Deep belief networks hold great promise for the simulation of human cognition because they show how structured and abstract representations may emerge from probabilistic unsupervised learning. These networks build a hierarchy of progressively more complex distributed representations of the sensory d...

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Bibliographic Details
Main Authors: Alberto eTestolin, Ivilin eStoianov, Michele eDe Filippo De Grazia, Marco eZorzi
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-05-01
Series:Frontiers in Psychology
Subjects:
Computer Simulation
MATLAB
Cognitive Modeling
unsupervised learning
Parallel architectures
deep neural networks
Online Access:http://journal.frontiersin.org/Journal/10.3389/fpsyg.2013.00251/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fpsyg.2013.00251/full

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