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A fast and simple algorithm for training neural probabilistic language models Andriy Mnih Gatsby Computational Neuroscience Unit, University College London
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Document Date: 2012-06-07 13:20:52

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City

Edinburgh / /

Company

Neural Information Processing Systems / PPL / Neural Networks / Weston / Penn Treebank / Microsoft / /

Country

United Kingdom / Scotland / /

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Facility

University College London amnih@gatsby.ucl.ac.uk Yee Whye Teh Gatsby Computational Neuroscience Unit / University College / /

IndustryTerm

energy function / information retrieval systems / natural language processing applications / dot product / natural language processing / computing / language processing / learning algorithm / /

Organization

Gatsby Charitable Foundation / University College London / International Speech Communication Association / University College London amnih@gatsby.ucl.ac.uk Yee Whye Teh Gatsby Computational Neuroscience Unit / Andriy Mnih Gatsby Computational Neuroscience Unit / Association for Computational Linguistics / /

Person

Vinayak Rao / Lloyd Elliot / Yee Whye Teh Gatsby Computational / /

Position

author / probabilistic model for semantic word vectors / language model / making the context bidirectional / model distribution moves / /

Product

Pentax K-x Digital Camera / Punkt / /

ProgrammingLanguage

Python / ML / /

PublishedMedium

Computational Linguistics / Machine Learning / Journal of Machine Learning Research / /

Technology

Neuroscience / learning algorithm / speech recognition / natural language processing / neural network / proposed algorithm / artificial intelligence / machine translation / Training algorithm / NCE algorithms / Pdh / Machine Learning / /

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