Explaining variational approximations

Ormerod, JT; Wand, MP

Explaining variational approximations

Ormerod, JT Wand, MP

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Publication Type:: Journal Article
Citation:: American Statistician, 2010, 64 (2), pp. 140 - 153
Issue Date:: 2010-05-01

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Field	Value	Language
dc.contributor.author	Ormerod, JT	en_US
dc.contributor.author	Wand, MP https://orcid.org/0000-0003-2555-896X	en_US
dc.date.issued	2010-05-01	en_US
dc.identifier.citation	American Statistician, 2010, 64 (2), pp. 140 - 153	en_US
dc.identifier.issn	0003-1305	en_US
dc.identifier.uri	http://hdl.handle.net/10453/13019
dc.description.abstract	Variational approximations facilitate approximate inference for the parameters in complex statistical models and provide fast, deterministic alternatives to Monte Carlo methods. However, much of the contemporary literature on variational approximations is in Computer Science rather than Statistics, and uses terminology, notation, and examples from the former field. In this article we explain variational approximation in statistical terms. In particular, we illustrate the ideas of variational approximation using examples that are familiar to statisticians. © 2010 American Statistical Association.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0877055
dc.relation.ispartof	American Statistician	en_US
dc.relation.isbasedon	10.1198/tast.2010.09058	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.title	Explaining variational approximations	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	64	en_US
utslib.for	0104 Statistics	en_US
dc.location.activity	Taipei, TAIWAN
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	64	en_US

Abstract:

Variational approximations facilitate approximate inference for the parameters in complex statistical models and provide fast, deterministic alternatives to Monte Carlo methods. However, much of the contemporary literature on variational approximations is in Computer Science rather than Statistics, and uses terminology, notation, and examples from the former field. In this article we explain variational approximation in statistical terms. In particular, we illustrate the ideas of variational approximation using examples that are familiar to statisticians. © 2010 American Statistical Association.

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http://hdl.handle.net/10453/13019