StatLearn 2010 - Workshop on "Challenging problems in Statistical Learning"

4 December 2014 · 47 min 24 s

1.1 Ultrametric wavelet regression of multivariate time series: application to Colombian conflict analysis (Fionn Murtagh)

We first pursue the study of how hierarchy provides a well-adapted tool for the analysis of change. Then, using a time sequence-constrained hierarchical clustering, we develop the practical aspects of a new...

4 December 2014 · 49 min 19 s

1.2 On the regularization of Sliced Inverse Regression (Stéphane Girard)

Sliced Inverse Regression (SIR) is an effective method for dimension reduction in highdimensional regression problems. The original method, however, requires the inversion of the predictors covariance matrix. In case of collinearity between...

4 December 2014 · 1 h

1.3 Simultaneous Gaussian Model-Based Clustering for Samples of Multiple Origins (Christophe Biernacki)

Mixture model-based clustering usually assumes that the data arise from a mixture population in order to estimate some hypothetical underlying partition of the dataset. In this work, we are interested in the...

4 December 2014 · 55 min 10 s

2.1 Mixed-Membership Stochastic Block-Models for Transactional Data (Hugh Chipman)

Transactional network data arise in many fields. Although social network models have been applied to transactional data, these models typically assume binary relations between pairs of nodes. We develop a latent mixed...

4 December 2014 · 57 min 11 s

2.2 Visualization of graphs by organized clustering : application to social and biological networks (Nathalie Villa-Vialaneix)

A growing number of applicative fields generate data that are pairwise relations between the objects under study instead of attributes associated to every object : social networks (relations between persons), biology (interactions...

4 December 2014 · 49 min 47 s

2.3 A Mixture of Experts Latent Position Cluster Model for Social Network Data (Claire Gormley)

Social network data represent the interactions between a group of social actors. Interactions between colleagues and friendship networks are typical examples of such data. The latent space model for social network data...

4 December 2014 · 56 min 5 s

3.1 Estimator selection with unknown variance (Christophe Giraud)

We consider the problem of Gaussian regression (possibly in a high- dimensional setting) when the noise variance is unknown. We propose a procedure which selects within any collection of estimators, an estimator...

4 December 2014 · 53 min 33 s

3.2 Regularization Methods for Categorical Predictors (Gerhard Tutz)

The majority of regularization methods in regression analysis has been designed for metric predictors and can not be used for categorical predictors. A rare exception is the group lasso which allows for...

4 December 2014 · 29 min 46 s

3.3 Importance sampling methods for Bayesian discrimination between embedded models (Jean-Michel Marin)

We survey some approaches on the approximation of Bayes factors used in Bayesian model choice and propose a new one. Our focus here is on methods that are based on importance sampling...

4 December 2014 · 1 h

4.1 High-dimensional interventions and causality : some results and many unsolved problems (Peter Bühlmann)

Understanding cause-effect relationships between variables is of interest in many fields of science. To effectively address such questions, we need to look beyond the framework of variable selection or importance from models...