Workshop: Post-selection Inference and Multiple Testing
From Feb 7, 2018 (2 pm) to Feb 9, 2018 (12:30 pm).
The number and size of available data sets of different types has increased dramatically over the past twenty years. This increase has triggered a shift from hypothesis-driven research to data-driven research in many scientific areas. The recent fields of selective inference and post-selection inference aim at developing mathematically sound frameworks to provide confidence statements on findings that may have undergone selection effects (cherry-picking). This is particularly challenging in biomedical sciences and neuro-imaging, where the data are typically heterogeneous and complex.
The goal of this workshop is to discuss these challenges and present dedicated innovative approaches and their applications.
- Yuval Benjamini (University of Jerusalem, Israel)
- Andreas Buja (Warthon University, USA)
- Jelle Goeman (University of Leiden, the Netherlands)
- Ruth Heller (University of Tel-Aviv, Israel)
- Nikolaos Ignatiadis (Stanford University, USA)
- Matthieu Lerasle (Université Paris-Sud and CNRS, France)
- Amit Meir (University of Washington, USA)
- David Preinerstorfer (Université Libre de Bruxelles, Belgium)
- Aldo Solari (University of Milano-Bicocca, Italy)
post-selection inference -- selective inference -- multiple testing -- multi-scale data -- genomics -- neuro-imaging
Registration for the workshop is free but mandatory.
Please note that limited funding will be available for selected students. To apply, please register by Friday, December 15.
Mélisande Albert (INSA Toulouse, Institut de Mathématiques de Toulouse)
Gilles Blanchard (Universität Potsdam, Institut für Mathematik)
Pierre Neuvial (CNRS, Institut de Mathématiques de Toulouse)
Etienne Roquain (Université de Paris 6, Laboratoire de Probabilités et Modèles Aléatoires)