We introduce a new estimator, the simultaneous multiscale change point estimator SMUCE,
for the change point problem in exponential family regression. An unknown step function is …

It has become routine to collect data that are structured as multiway arrays (tensors). There
is an enormous literature on low rank and sparse matrix factorizations, but limited …

We observe a N× M matrix of independent, identically distributed Gaussian random
variables which are centered except for elements of some submatrix of size n× m where the …

The main goal in this paper is to propose a new approach to deriving oracle inequalities
related to the exponential weighting method. The paper focuses on recovering an unknown …

The paper is concerned with recovering an unknown vector from noisy data with the help of
a family of ordered smoothers [11]. The estimators within this family are aggregated based …

This thesis is devoted to the study of both theoretical and practical properties of various
aggregation techniques. We first extend the PAC-Bayesian theory to the high dimensional …

The aim of this habilitation thesis is to give an overview of my works on high-dimensional
statistics and statistical learning, under various sparsity assumptions. In a first part, I will …

Résumé Ce mémoire d'habilitation a pour objet diverses contributions à l'estimation et à
l'apprentissage statistique dans les modeles en grande dimension, sous différentes …

Substantial progress has been achieved over the last years in estimating very
highdimensional regression models. A thorough introduction to this dynamic field of …