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On the difficulty of training Recurrent Neural Networks Razvan Pascanu Universite de Montreal [removed]
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Document Date: 2013-02-19 02:24:57


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Martigny / San Francisco / Montreal / Nottingham / New York / /

Company

Echo State Networks / AA AB BA / LG / IEEE Press / Neural Networks / GPU / Penn Treebank / Perseus Books Group / Recurrent Neural Networks / /

Country

Switzerland / Jordan / United States / /

Currency

SGD / /

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Event

Man-Made Disaster / /

Facility

Brno University of Technology / /

IndustryTerm

input-less recurrent network / recurrent networks / state networks / online learning / generator network / well understood solution / autonomous systems / recurrent network / secondorder algorithms / hidden unit recurrent network / sum-of-products / Reservoir computing / dynamical systems / dynamical systems tools / recurrent gas market model / not be analyzed using standard dynamical systems tools / /

Organization

Yoshua Bengio Universite de Montreal / Recurrent Neural Networks Razvan Pascanu Universite / international speech communication association / US Federal Reserve / Brno University of Technology / Pattern Analysis and Machine Intelligence / /

Person

Frederic Bastien / Tomas Mikolov / James Bergstra / Pascal Lamblin / Morgan Kaufmann / /

Position

teacher / Singer / neurodynamical model for working memory / model for each time step / /

ProgrammingLanguage

E / Python / T / /

ProvinceOrState

Utah / New York / /

PublishedMedium

IEEE Transactions on Pattern Analysis and Machine Intelligence / Machine Learning / Journal of Machine Learning Research / /

Technology

This algorithm / neural network / SGD-C algorithms / Machine Learning / simulation / midi / pdf / secondorder algorithms / /

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http /

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