Workshop: Post-selection Inference and Multiple Testing
From Feb 7, 2018 (2 pm) to Feb 9, 2018 (12 noon).
- Feb 7: invited talks (2 pm - 5 pm); poster session (5 pm - 7 pm)
- Feb 8: invited talks (9 am - 12 pm); lunch (12 pm: 2 pm); invited talks (2 pm - 5 pm)
- Feb 9: invited talks (9 am - 12 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.
- Jean-Marc Azaïs (IMT, University of Toulouse)
- Yuval Benjamini (University of Jerusalem, Israel)
- Andreas Buja (The Wharton School, University of Pennsylvania, 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)
- Aaditya Ramdas (University of California at Berkeley)
- 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.
- Mélisande Albert (Institut de Mathématiques de Toulouse, INSA Toulouse)
- Gilles Blanchard (Universität Potsdam, Institut für Mathematik)
- Pierre Neuvial (Institut de Mathématiques de Toulouse, University of Toulouse)
- Etienne Roquain (Université de Paris 6, Laboratoire de Probabilités et Modèles Aléatoires)
Contact: Pierre Neuvial