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Penalized empirical risk minimization and sparse recovery problems

Date: 
Thursday 26th June 2008 - 10:00 to 11:00
Venue: 
INI Seminar Room 1
Session Chair: 
Sasha Tsybakov
Abstract: 

A number of problems in regression and classification can be stated as penalized empirical risk minimization over a linear span or a convex hull of a given dictionary with convex loss and convex complexity penalty, such as, for instance, $\ell_1$-norm. We will discuss several oracle inequalities showing how the error of the solution of such problems depends on the "sparsity" of the problem and the "geometry" of the dictionary.

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Presentation Material: 
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons