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Computational statistics / Stochastic optimization / Statistical mechanics / Estimation theory / Markov chain Monte Carlo / Langevin dynamics / Stochastic approximation / Metropolis–Hastings algorithm / Mixture model / Statistics / Probability and statistics / Monte Carlo methods


Bayesian Learning via Stochastic Gradient Langevin Dynamics
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Document Date: 2011-05-21 11:48:52

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File Size: 284,43 KB

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Company

Neural Information Processing Systems / Neural Networks / S. S. Trust / Monte Carlo / CRC Press / /

Country

United States / /

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Facility

Queen Square / University of California / /

IndustryTerm

internet traffic / inference algorithm / efficient stochastic gradient ascent algorithm / online parameter estimation / online average / natural language processing / dynamics algorithm / type algorithms / fixed-point algorithms / online setting / online estimation / dynamical systems / stochastic gradient algorithms / stochastic gradient optimization algorithm / /

Organization

School of Information and Computer Science / Gatsby Charitable Foundation / National Science Foundation / USA Yee Whye Teh ywteh@gatsby.ucl.ac.uk Gatsby Computational Neuroscience Unit / University of California / Irvine / /

Person

Max Welling / /

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Position

author / Fisher / /

Product

Hamiltonian / Langevin / Altec XT1 Speakers / /

ProgrammingLanguage

ML / /

PublishedMedium

Machine Learning / Journal of Machine Learning Research / /

Technology

ICA algorithm / Neuroscience / sampling algorithms / LAN / two sampling algorithms / stochastic gradient algorithms / bioinformatics / stochastic gradient Langevin algorithm / natural language processing / av / stochastic gradient optimization algorithm / stochastic Langevin algorithm / fixed-point algorithms / inference algorithm / stochastic gradient Langevin dynamics algorithm / efficient stochastic gradient ascent algorithm / machine learning / html / Langevin dynamics MH algorithm / Robbins-Monro type algorithms / /

URL

http /

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