![Statistics / Mathematical analysis / Regularization / Tikhonov regularization / Learning / Supervised learning / Mathematical optimization / Least squares / Reinforcement learning / Machine learning / Mathematics / Linear algebra Statistics / Mathematical analysis / Regularization / Tikhonov regularization / Learning / Supervised learning / Mathematical optimization / Least squares / Reinforcement learning / Machine learning / Mathematics / Linear algebra](https://www.pdfsearch.io/img/c02881d3b29cb3779fd12505a2386ca5.jpg)
| Document Date: 2012-06-07 13:20:38 Open Document File Size: 548,75 KBShare Result on Facebook
City Nancy / Parr / Wakefield / C. / Edinburgh / / Company MIT Press / / Country France / United Kingdom / Scotland / / Currency pence / / / 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 / / URL http /
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