Workshop on "Challenging problems in Statistical Learning"
January 28-29, 2010
Université Paris 1 Panthéon-Sorbonne
Centre Malher, 9 rue Malher, Paris 4ème, France
News : the videos of talks given at the workshop are now available online at http://epi.univ-paris1.fr/samm-statlearn
The workshop on "Challenging problems in Statistical Learning" will be held in Paris on January 28-29, 2010. This workshop aims to summarize the new and future problems in statistical learning and to give a good idea of what already exists for dealing with these problems. This event is co-organized by the University Paris 1 Panthéon-Sorbonne and INRIA Saclay - Ile de France.
- Session 1 (Thursday 9h-12h30) : Statistical learning and complex data
- F. Murtagh (University of London) : Ultrametric wavelet regression of multivariate time series : application to Colombian conflict analysis.
- S. Girard (INRIA Rhône-Alpes) : On the regularization of Sliced Inverse Regression.
- C. Biernacki (Université Lille 1) : Simultaneous Gaussian Model-Based Clustering for Samples of Multiple Origins.
- Session 2 (Thursday 14h-17h30) : Learning with social networks
- H. Chipman (Acadia University, Canada) : Mixed-Membership Stochastic Block-Models for Transactional Data.
- N. Villa (Inst. de Mathématiques de Toulouse & IUT de Carcassonne) : Visualization of graphs by organized clustering : application to social and biological networks.
- C. Gormley (University College Dublin) : A Mixture of Experts Latent Position Cluster Model for Social Network Data.
- Session 3 (Friday 9h-12h30) : Regularization and model selection
- G. Tutz (University of Munich) : Regularization Methods for Categorical Predictors.
- J.-M. Marin (Université Montpellier 2) : Importance sampling methods for Bayesian discrimination between embedded models.
- C. Giraud (Ecole Polytechnique) : Estimator selection with unknown variance.
- Session 4 (Friday 14h-17h30) : New and future problems in statistical learning
- P. Buhlmann (Federal Institute of Technology Zurich) : High-dimensional interventions and causality : some results and many unsolved problems.
- S. Robin (AgroParisTech) : Statistical analysis of bio-molecular data and combinatorial difficulties : two examples.
- S. Arlot (CNRS & ENS Paris) : Data-driven penalties for optimal calibration of learning algorithms.
Registration : registration is free of charge until January 15, 2010 and should be done trough the registration form below.