Validation in Statistics and Machine Learning

6-7 October 2010

Titles and Abstracts

Christoph Bernau
Correction for Tuning Bias in Resampling Based Error Rate Estimation
abstract

Anne-Laure Boulesteix
Over-optimism in statistical bioinformatics: an illustration
abstract

Mikio L. Braun
Machine Learning Open Source Software and Benchmark Repository
abstract

Thorsten Dickhaus
How normal can the t-statistic possibly be?
abstract

Manuel Eugster
Sequential Benchmarking
abstract

Francois Fleuret
The MASH platform - Collaborative design of large-scale learning architectures
abstract

Thomas A. Gerds
Confidence scores for prediction models
abstract

Jelle Goeman
Fast approximate leave-one-out cross-validation for large sample sizes
abstract

Ulrike Grömping
Variable Importance in Linear Models and Random Forests
abstract

Torsten Hothorn
Reproducible Statistical Analyses Today
abstract

Niels Keiding
Reproducible research and the substantive context
abstract

Jean-Charles Lamirel
Use of distance-based indexes might well lead to misinterpretation of clustering quality results
abstract

Neil Lawrence
Validation in Statistics and Machine Learning
abstract

Ulrich Mansmann
Biological aspects for the validation of estimated gene interaction networks from microarray data
abstract

Andreas Mayr
The correct validation of prediction intervals
abstract

Renee Menezes
Filtering, FDR and bias in high-dimensional data analysis
abstract

Hans-Joachim Mucha
Validation in cluster analysis
abstract

Tsuyoshi Okita
Statistical Significance Test in Machine Translation
abstract

Julia Schiffner
Bias-Variance Analysis of Local Classification Methods
abstract

François Schnitzler
Discussing the validation of high-dimensional probability distribution learning with mixtures of graphical models for inference
abstract

Carolin Strobl
What we can learn from trees and forests
abstract

Caroline Truntzer
Comparative optimism in models involving both classical clinical and gene expression information
abstract

Richardus Vonk
The Many Faces of Validation
abstract

Verena Zuber
High-dimensional feature selection by decorrelation
abstract