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Learning / Corpus linguistics / Theoretical computer science / Treebank / Boosting / Parsing / Michael Collins / Supervised learning / Structured prediction / Machine learning / Artificial intelligence / Ensemble learning


Simple Training of Dependency Parsers via Structured Boosting Qin Iris Wang Department of Computing Science University of Alberta
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Document Date: 2006-12-29 14:43:25


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City

Ann Arbor / /

Company

Chinese Treebank / Treebank / Dekang Lin Google Inc. / English Penn Treebank / Penn Treebank / /

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Facility

Computing Science University / Prentice Hall / /

IndustryTerm

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Organization

Alberta Ingenuity Centre for Machine Learning / Structured Boosting Qin Iris Wang Department / U.S. Securities and Exchange Commission / University of Alberta / Dale Schuurmans Department / /

Person

Cherry / Dayne Freitag / David Magerman / D. Schuurmans / C. Cherry / Ryan McDonald / Fernando Pereira / Robert E. Schapire / Yoram Singer / Heidi J. Fox / Q. Wang / Koby Crammer / D. Lin / Qin Iris Wang / Andrew McCallum / D. Lizotte / Dan Bikel / Joshua Goodman / Dale Schuurmans / /

Position

Singer / VP Figure / VP NP VP / VP NP PP NP NNS VBP TO VB NN IN NN NNS Investors / Statistical decisiontree model for parsing / /

Product

Dependency Parsing Since / /

ProvinceOrState

Michigan / /

PublishedMedium

Computational Linguistics / Machine Learning / /

Technology

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