The INI has a new website!

This is a legacy webpage. Please visit the new site to ensure you are seeing up to date information.

Skip to content



Penalized empirical risk minimization and sparse recovery problems

Koltchinskii, V (Georgia Institute of Technology)
Thursday 26 June 2008, 10:00-11:00

Seminar Room 1, Newton Institute


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.




The video for this talk should appear here if JavaScript is enabled.
If it doesn't, something may have gone wrong with our embedded player.
We'll get it fixed as soon as possible.

Back to top ∧