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MIT OCW High-Dimensional Statistics (Spring 2015)
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This course offers an introduction to the finite sample analysis of high- dimensional statistical methods. The goal is to present various proof techniques for state-of-the-art methods in regression, matrix estimation and principal component analysis (PCA) as well as optimality guarantees. The course ends with research questions that are currently open. Taught by Prof. Philippe Rigollet. |
statistics |
Submitted by elementlist on Feb 07, 2017 |
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