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Graphical models / Bayesian statistics / Machine learning / Tree traversal / Generative model / Bayesian network / Latent variable / Hidden Markov model / N-gram / Statistics / Statistical models / Probability


Structured Generative Models of Natural Source Code Chris J. Maddison† University of Toronto CMADDIS @ CS . TORONTO . EDU
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Document Date: 2015-02-01 17:03:28

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City

Beijing / TORONTO / /

Company

The MIT Press / IEEE Press / Microsoft / /

Country

Jordan / China / /

Facility

Maddison† University of Toronto CMADDIS / University of California / /

IndustryTerm

machine learning technologies / massive open online courses / public online repositories / mining / computing / related applications / software engineering community / learning tools / code completion tools / energy / /

Organization

MIT / University of California / Berkeley / Natural Source Code Chris J. Maddison† University of Toronto CMADDIS / /

Person

Yoram / Yee Whye / Chris J. Maddison / Charles Sutton / Daniel Conrad / Anh Tuan / Hung Viet / Ruslan R. Reducing / Hoan Anh / Miltos Allamanis / Andy Gordon / Charles A. Mining / John Winn / Tom Minka / Tree Traversal / Thore Graepel / Daniel Tarlow / Christopher D. Fast / /

Position

author / tackle / designer / model for natural language parsing / model for LTTs / model for software bug finding / Fisher / forward / General / model for source code / /

ProgrammingLanguage

Java / R / C / C++ / /

ProvinceOrState

California / /

PublishedMedium

Machine Learning / Journal of Machine Learning Research / /

Technology

functional programming / natural language processing / Java / API / http / machine learning technologies / machine learning / /

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