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Bayesian statistics / Econometrics / Regression analysis / Maximum likelihood / Logistic regression / Supervised learning / Order statistic / Akaike information criterion / Statistical model / Statistics / Statistical theory / Estimation theory


Probabilistic n-Choose-k Models for Classification and Ranking Kevin Swersky Daniel Tarlow Dept. of Computer Science
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Document Date: 2012-11-13 03:36:57

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Company

Neural Information Processing Systems / /

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Facility

A. Diwan / Group University / Computer Science University / Computer Science University of Toronto / /

IndustryTerm

energy function / inner product / divide-and-conquer algorithm / approximate energy minimization / learning-to-rank applications / binary algorithm / web search / dynamic programming algorithm / dynamic programming algorithms / Statistical applications / tree algorithm / learning algorithm / /

Organization

School of Eng / Harvard University / University of Toronto / /

Person

Richard S. Zemel / Kevin Swersky Daniel Tarlow / Brendan J. Frey Prob / /

ProgrammingLanguage

R / /

PublishedMedium

Machine Learning / Journal of Machine Learning Research / /

Technology

learning algorithm / binary algorithm / dynamic programming algorithms / dynamic programming algorithm / machine learning / FFT tree algorithm / divide-and-conquer algorithm / /

URL

http /

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