Hi, 

just a quick reminder:

Tuesday 15th at 11:00 we will have a presentation by Yves Grandvalet from Heudiasyc labs at UTC Compiègne near Paris. 

Title : Beyond Support in Two-Stage Variable Selection
Room: AA3195

Abstract:
Numerous variable selection methods rely on a two-stage procedure, where a
sparsity-inducing penalty is used in the first stage to predict the support,
which is then conveyed to the second stage for estimation or inference
purposes.  In this framework, the first stage screens variables to find a set
of possibly relevant variables and the second stage operates on this set of
candidate variables, to improve estimation accuracy or to assess the
uncertainty associated to the selection of variables.

We advocate that more information can be conveyed from the first stage to the
second one: we use the magnitude of the coefficients estimated in the first
stage to define an adaptive penalty that is applied at the second stage.

We give the example of an inference procedure that highly benefits from the
proposed transfer of information.
The procedure is precisely analyzed in a simple setting, and our large-scale
experiments empirically demonstrate that actual benefits can be expected in 
much more general situations, with sensitivity gains ranging from 50% to
100% compared to state-of-the-art.

Keywords: Linear model, Lasso, Variable selection, p-values, False
discovery rate, Screen and clean.