Call for posters: Workshop on Validation in Statistics and Machine Learning

October, 6 – 7, 2010
WIAS Berlin, Germany

— Important dates —

* submission deadline (posters): 31 Aug
* notification of submissions : 08 Sep
* registration deadline : 22 Sep

— Overview —

In statistics and machine learning, the evaluation of algorithms
typically relies on their performance on data. This is because, in
contrast to a theoretical guarantee (e.g. a consistency result), it is
in general not possible to prove that an algorithm performs well on a
particular (unseen) data set. Therefore, it is of vital importance that
we ensure the reliability of data-based evaluations. This requirement
poses a wide range of open research problems and challenges. These include

* the lack of a ground truth to validate results in real-world
* the high instability of empirical results in many settings,
* the difficulty to make statistics and machine learning research
* the general over-optimism of published research findings due
pre-publication optimization of the algorithms and publication bias.

This workshop brings together scientists from statistics, machine
learning, and their application fields to tackle these challenges. The
workshop serves as a platform to critically discuss current
shortcomings, to exchange new approaches, and to identify promising
future directions of research.

We invite poster submissions that fit into the scope and topics of the

The workshop is funded by the Weierstrass Institute (WIAS) Berlin and by
the Pascal2 Network of Excellence.

Invited speakers include:

Mikio L. Braun (TU Berlin)
Thorsten Dickhaus (HU Berlin)
Francois Fleuret (EPF Lausanne / IDIAP)
Thomas A. Gerds (University of Copenhagen)
Jelle Goeman (Leiden University)
Ulrike Grömping (Beuth University of Applied Sciences Berlin)
Torsten Hothorn (LMU Munich)
Niels Keiding (University of Copenhagen)
Ulrich Mansmann (LMU Munich)
Carolin Strobl (LMU Munich)
Richardus Vonk (Bayer-Schering Pharma)

— Organization —

Nicole Krämer (WIAS Berlin)
Anne-Laure Boulesteix (University of Munich)