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Decision theory / Econometrics / Loss function / Maximum spacing estimation / Statistics / Statistical theory / Estimation theory


Statistical linear estimation with penalized estimators: an application to reinforcement learning ´ Bernardo Avila Pires
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Document Date: 2012-06-07 13:20:34

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City

Belmont / Edmonton / Cambridge / Lille / Edinburgh / /

Company

Neural Information Processing Systems / MIT Press / Oracle / parametric sA / /

Country

United Kingdom / Scotland / /

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Facility

University of Alberta / /

Holiday

Assumption / /

IndustryTerm

on-line learning algorithms / conditioned systems / approximate solution / Linear least-squares algorithms / analytic tools / /

Organization

Royal Statistical Society / MIT / Department of Computing Science / University of Alberta / /

Person

Bradford Book / Csaba Szepesv / Xt / Bernardo Avila Pires / /

Position

transition kernel PM / author / Prime Minister / Rt / steady-state distribution underlying PM / /

ProgrammingLanguage

R / C / /

ProvinceOrState

Alberta / Massachusetts / /

PublishedMedium

Journal of the Royal Statistical Society / Machine Learning / IEEE Transactions on Information Theory / Journal of Machine Learning Research / /

Technology

Linear least-squares algorithms / artificial intelligence / tomography / on-line learning algorithms / Machine Learning / LSTD algorithm / /

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