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Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions Richard Socher Jeffrey Pennington∗ Eric H. Huang Andrew Y. Ng Christopher D. Manning Computer Science Department, Stanford University, Stanf
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Document Date: 2011-06-22 03:47:41

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Company

Wilson / Weston / Air Force Research Laboratory / Experience Project / /

Country

Jordan / United States / Lebanon / /

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Facility

Stanford University / /

IndustryTerm

neural network / autoencoder network / external systems / recurrent neural networks / positive/negative product / neural networks / large web graph / recursive neural networks / beam search algorithms / social networks / computing / parked car / food / /

MusicAlbum

Sorry / /

Organization

Defense Advanced Research Projects Agency / Predicting Sentiment Distributions Richard Socher Jeffrey Pennington∗ Eric H. Huang Andrew Y. Ng Christopher D. Manning Computer Science Department / US government / Harvard / Stanford University / idf / U.S. Securities and Exchange Commission / /

Person

EP EP / Jiquan Ngiam / Gabor Angeli / Quoc Le / Chris Potts / Bozhi See / Christopher D. Manning / Alan Wu / Raymond Hsu / Andrew Maas / Eric H. Huang / Semi-Supervised Recursive Autoencoders / Richard Socher Jeffrey Pennington / /

Position

author / teacher / /

Product

Pentax K-x Digital Camera / C-0181 / /

ProgrammingLanguage

J / K / /

PublishedMedium

Journal of Machine Learning Research / /

SportsLeague

Stanford University / /

Technology

neural network / CKY-like beam search algorithms / machine learning / /

URL

www.cs.pitt.edu/mpqa / www.experienceproject.com / http /

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