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Contribution to statistical learning of complex data using generative models
This manuscript presents my research activities, which mainly focus on designing parametric, parsimonious and meaningful generative models for complex data. Several... -
Sample dispersion is better than sample discrepancy for classification
We want to generate learning data within the context of active learning. First, we recall theoretical results proposing discrepancy as a criterion for generating... -
Linear and convex aggregation of density estimators
To appear in Mathematical Methods of Statistics -
Affine Invariant Shape Description Using the Triangular Kernel
We present in this report a novel approach for shape description based on kernel principal component analysis (KPCA). The strength of this method resides in the affine... -
Coping with the Computational and Statistical Bipolar Nature of Machine Learning
Machine Learning is known to have its roots in a broad spectrum of fields including Artificial Intelligence, Pattern Recognition, Statistics or Optimisation. From the... -
Non-asymptotic approach to varying coefficient model
In the present paper we consider the varying coefficient model which represents a useful tool for exploring dynamic patterns in many applications. Existing methods... -
Reconstruction of proteomic profiles for biomarker discovery
This thesis has been prepared at the CEA Léti, Minatec Campus, (Grenoble, France) and the IMS (Bordeaux, France) in the field of information and signal processing of... -
Process modeling and control using artificial neural networks: application to...
Artificial neural networks allow the construction of a wide family of nonlinear models and controllers using statistical learning. The purpose of this thesis is to... -
Texture Classification By Statistical Learning From Morphological Image Proce...
International audience -
Procedural learning across modalities in French speaking children with specif...
International audience -
Toric grammars: a new statistical approach to natural language modeling
We propose a new statistical model for computational linguistics. Rather than trying to estimate directly the probability distribution of a random sentence of the... -
Variational methods for model-based image segmentation - applications in medi...
Within the wide field of medical imaging research, image segmentation is one of the earliest but still open topics. This thesis focuses on model-based segmentation... -
Supervised metric learning with generalization guarantees
In recent years, the crucial importance of metrics in machine learningalgorithms has led to an increasing interest in optimizing distanceand similarity functions using... -
Active learning for variety approximation
Statistical learning aims to modelize a functional link between two variables X and Y thanks to a random sample of realizations of the couple (X,Y ). When the variable... -
Improving offline evaluation of contextual bandit algorithms via bootstrappin...
International audience -
Statistical modeling of maternal and neonatal mortality for help in planning ...
The aim of this thesis is to design a supervised statistical learning methodology that can overcome the weakness of standard methods when the prior distribution of the...
