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Bayesian statistics / Econometrics / Bayesian inference / Expectation–maximization algorithm / Loss function / Kullback–Leibler divergence / Bayes estimator / Marginal likelihood / Maximum likelihood / Statistics / Estimation theory / Statistical theory


Approximate inference for the loss-calibrated Bayesian Simon Lacoste-Julien University of Cambridge 1
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Document Date: 2011-12-02 09:14:29

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Cambridge / Springer / Fort Lauderdale / /

Company

MIT Press / Monte Carlo / CRC Press / /

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Jordan / United States / /

Event

Environmental Issue / /

Facility

Aston University / University College London / Massachusetts Institute of Technology / Bayesian Simon Lacoste-Julien University of Cambridge / The plant / University of Cambridge Zoubin Ghahramani University / /

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conjugate gradient algorithm / variational inference algorithm / approximate sparse solution / loss-calibrated approximate inference algorithms / valid coordinate ascent algorithm / typical supervised learning applications / variational algorithm / approximate inference algorithm / learning algorithm / /

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Gatsby Computational Neuroscience Unit / Royal Statistical Society / University College London / American Statistical Association / Department of Statistical Science / MIT / Bayesian Simon Lacoste-Julien University of Cambridge / Massachusetts Institute of Technology / U.S. Securities and Exchange Commission / Cambridge Zoubin Ghahramani University of Cambridge Abstract / Aston University / /

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Gq / Simon Lacoste-Julien / Learning / /

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editor / General / /

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RPD / /

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New York / Massachusetts / /

PublishedMedium

Journal of the Royal Statistical Society / Journal of Machine Learning Research / Journal of the American Statistical Association / /

Technology

Neuroscience / variational inference algorithm / learning algorithm / approximate inference algorithm / loss-calibrated EM algorithm / loss-calibrated approximate inference algorithms / EM-like algorithm / loss-EM algorithm / variational algorithm / artificial intelligence / variational EM algorithm / loss-EM algorithms / GPS / particular EM algorithm / conjugate gradient algorithm / machine learning / linearized loss-EM algorithm / loss-calibrated Bayesian tional Expectation-Maximization algorithm / EM algorithm / valid coordinate ascent algorithm / /

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