[Lisa_teatalk] Talk by Yves Grandvalet on Tuesday, 15th December, 11am

Jörg Bornschein bornj at iro.umontreal.ca
Sat Dec 5 17:24:58 EST 2015


Hi,

we are going to have Yves Grandvalet visiting on Monday 14th and Tuesday
15th, i.e. just after NIPS.

Yves is the head of the Heudiasyc lab (where Antoine Bordes and Nicolas
Usunier worked before they joined Facebook), and a past collaborator of
LISA (he spent a few months at LISA a couple of years ago). He's would also
like to discuss possible collaboration avenues between our labs (maybe just
after his talk).

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Title : Beyond Support in Two-Stage Variable Selection
Who: Yves Grandvalet
When: Tuesday, 15th, 11am
Where: 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.
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