## SFB 649 "Economic Risk" - C.A.S.E. -
PASCAL - WIAS

### Workshop on

#### [ Friday and Saturday, Dec. 5 &
6, 2008 ]

#### Background

Data sets with a very large number of explanatory variables are
becoming more and more common as features of both applications and
theoretical investigations. In economical applications for instance,
the revealed preference of market players is observed, and the analyst
tries to understand them by a complex model by which the players'
behavior can be understood as an indirect observation.
State-of-the
art statistical approaches often formulate such models as inverse
problems, but the corresponding methods can suffer of the curse of
dimensionality: when there are "too many" possible explanatory
variables, additional regularization is needed. Inverse problem theory
already offers sophisticated regularization methods for smooth models,
but is just beginning to integrate sparsity concepts. For
high-dimensional linear models, sparsity regularizations have proved to
be a convincing way to tackle the issue both in theory and
practice,
but there remains a vast ground to be explored.
Paralleling the
statistics community are also recent advances in machine learning
methodology and statistical learning theory, where the themes of
sparsity and inverse problems have been intertwined.

The workshop will focus on the different ways to attack a same
question: there are many potential models to choose from, but
each of
them is relatively simple - each model is parameterized by many
variables, most of them are zero. Yet, the choice of the right model or
regularization parameter is crucial to obtain stable and reliable
results.

.

The meeting will take place from Friday,
Dec. 5th,
morning to Saturday, Dec. 6th, early afternoon.

#### General Information

##### Location

Weierstrass Institute for Applied Analysis and Stochastic

Mohrenstr. 39

10117 Berlin Mitte

Germany
##### Organizing Committee

Gilles Blanchard, Wolfgang Härdle, Markus Reiß,
Ya'acov Ritov,
and Vladimir Spokoiny.

##### Administration

Ms. Andrea Fiebig:

Institute of Mathematics

Humboldt University

Unter den Linden 6,

D-10099 Berlin, Germany,

FAX no. +49 (0)30 2093 - 5848

Tel. +49 (0)30-2093-5860
#### Confirmed Invited Speakers

#### Registration

Registration fee is 100 Euro, 50 for students,
including
dinner and
coffee. The registration fee will be waved under some special
circumstances).
The number of participants is strictly limited. Deadline for
contributed talks is October 31st. Please fill in the registration form
[note: PDF] and send it by fax or postal mail to Andrea Fiebig
(information above).

#### Links