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Statistics / Mathematical analysis / Regularization / Tikhonov regularization / Learning / Supervised learning / Mathematical optimization / Least squares / Reinforcement learning / Machine learning / Mathematics / Linear algebra


A Dantzig Selector Approach to Temporal Difference Learning Matthieu Geist Sup´elec, IMS Research Group, Metz, France [removed]
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Document Date: 2012-06-07 13:20:38

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City

Nancy / Parr / Wakefield / C. / Edinburgh / /

Company

MIT Press / /

Country

France / United Kingdom / Scotland / /

Currency

pence / /

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Event

Product Recall / Product Issues / /

Facility

University of Alberta / /

IndustryTerm

sparse solution / joint operator / sparse solutions / similar solutions / regression algorithm / /

Organization

Royal Statistical Society / MIT / U.S. Securities and Exchange Commission / University of Alberta / French National Research Agency / /

Person

Alessandro Lazaric / Mohammad Ghavamzadeh / Bruno Scherrer / Matthieu Geist Sup´elec / /

Position

author / rt / Behrens-Fisher / first author / /

Product

TD / /

ProvinceOrState

Alberta / /

PublishedMedium

Journal of the Royal Statistical Society / Machine Learning / /

Technology

LSTD algorithms / Dantzig-LSTD algorithm / proposed algorithm / A. G. Linear Least-Squares algorithms / regression algorithm / LARS algorithm / known algorithm / Machine Learning / Temporal Difference Learning This algorithm / LSTD algorithm / 1 regularized algorithms / /

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http /

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