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Expectation–maximization algorithm / Dirichlet process / Mixture model / Latent Dirichlet allocation / Normal distribution / Factorial / Markov chain / Central limit theorem / Bayesian inference / Statistics / Bayesian statistics / Variational Bayesian methods


Collapsed Variational Dirichlet Process Mixture Models∗ Max Welling Kenichi Kurihara Dept. of Computer Science Dept. of Computer Science UC Irvine, USA
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Document Date: 2012-07-24 13:22:36

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City

Cambridge / /

Country

Jordan / /

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Facility

University of Amsterdam / Computer Science National University / University College London / USA Tokyo Institute of Technology / /

IndustryTerm

collapsed variational algorithms / inference algorithm / inference algorithms / approximate solution / data mining / variational algorithms / em algorithm / collapsed variational bayesian inference algorithm / /

Organization

Lee Kuan Yew Endowment Fund / University College London / National Science Foundation / National University of Singapore / American Statistical Association / University of Amsterdam / Department of Cognitive Neurology / Tokyo Institute of Technology / /

Person

Yee Whye Teh / Max Welling Kenichi Kurihara / /

ProgrammingLanguage

VB / /

ProvinceOrState

Massachusetts / /

PublishedMedium

Journal of the American Statistical Association / /

Technology

inference algorithms / stick-breaking VB algorithms / improved VB algorithm / six algorithms / variational algorithms / collapsed variational algorithms / collapsed variational bayesian inference algorithm / data mining / machine learning / variational Bayesian inference algorithm / em algorithm / six VB inference algorithms / /

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