9-13 November 2015
Europe/Zurich timezone
There is a live webcast for this event.

High-dimensional model estimation and model selection

12 Nov 2015, 14:00
222/R-001 (CERN)



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Christian Mueller (Simons Foundation)


I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.

Presentation Materials