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Sparse and discriminative clustering for complex data. An application to cyto...
The main topics of this manuscript are sparsity and discrimination for modeling complex data. In a first part, we focus on the GMM context: we introduce a new family... -
Structured Sparsity-Inducing Norms : Statistical and Algorithmic Properties w...
Numerous fields of applied sciences and industries have been witnessing a process of digitisation over the past few years. This trend has come with a steady increase... -
X-ray CT Image Reconstruction from Few Projections
To improve the safety (lower dose) and the productivity (faster acquisition) of an X-ray CT system, we want to reconstruct a high quality image from a small number of... -
Traitement des signaux parcimonieux et applications
Whatever the field of application, optimizing the results and sometimes even solving problems requires taking advantage of the whole prior information. In this... -
Petite mathématique du cerveau
International audience -
Contributions to the study of free bands detection in the context of Cognitiv...
The wireless communications systems continue to grow and has become very essential nowadays. This growth causes an increase in the demand of spectrum resources, which... -
Estimation de fonctions géométriques et déconvolution
The presented work is divided into three parts. At first, we show that the formalism of model selection allows to bound the decay rate of the estimation error of a... -
Hybrid dynamical system Identification: geometry, sparsity, and nonlinearities
In automatic control, obtaining a model is always the cornerstone of the synthesis procedures such as controller design, fault detection or prediction... This thesis... -
Estimation 3D jointe des volumes et des vitesses pour la tomographie PIV
National audience -
Contributions to statistical learning in sparse models
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... -
Aggregation of estimators and classifiers : theory and methods
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... -
Sparsity-based detection strategies for faint signals in noise : application ...
This thesis deals with the problem of detecting unknown signals at low Signal- to- Noise Ratio. This work focuses on the definition, study and implementation of... -
Sparse representations for multivariate signals
In this thesis, we study approximation and learning methods which provide sparse representations. These methods allow to analyze very redundant data-bases thanks to... -
Sparse Blind Deconvolution in Ultrasound Imaging Using an Adaptive CLEAN Algo...
The ultrasonic imaging knows a continuous advance in the aspect of increasing the resolution for helping physicians to better observe and distinguish the examined...
