THIS THESIS IS DOVOTED TO OPTIMAL QUANTIZATION WITH SOME APPLICATIONS TO MATHEMATICAL FINANCE. CHAP.1 REMINDS THE BASES OF OPTIMAL QUANTIZATION AND NUMERICAL SEARCH OF OPTIMAL QUANTIZERS. IN CHAP.2 WE STUDY THE ASYMPTOTICS, IN L^S, OF THE QUANTIZATION ERROR ASSOCIATED TO A LINEAR TRANSFORM OF AN L^R OPTIMAL SEQUENCE OF QUANTIZERS. WE SHOW THAT SUCH A TRANSFORMATION ALLOWS TO MAKE THE TRANSFORMED SEQUENCE L^S RATE OPTIMAL FOR EVERY S>0, FOR A LARGE FAMILY OF PROBABILITIES. CHAP.3 DEALS WITH THE ASYMPTOTICS OF THE MAXIMAL RADIUS SEQUENCE ASSOCIATED TO AN L^R OPTIMAL SEQUENCE OF QUANTIZERS. WE SHOW THAT AS SOON AS SUPP(P) IS UNBOUNDED, THE MAXIMAL RADIUS CONVERGE TO INFINITY. WE THEN GIVE THE RATE OF CONVERGENCE FOR A LARGE FAMILY OF PROBABILI...
30 pagesWe investigate the greedy version of the L^p-optimal vector quantization problem for an R^d-...
We present an introductory survey to optimal vector quantization and its first application...
We present an introductory survey to optimal vector quantization and its first application...
Cette thèse est divisée en quatre parties pouvant être lues indépendamment. Dans ce manuscrit, nous ...
This thesis is concerned with the study of optimal quantization and its applications. We deal with t...
31 pagesInternational audienceLet $P$ be a probability distribution on $\mathbb{R}^d$ (equipped with...
This thesis is concerned with the study of optimal quantization and its applications. We deal with t...
Dans la première partie, nous nous concentrons sur la quantification vectorielle gloutonne. Nous éta...
Nous développons une approche de résolution numérique du filtrage par méthode de grille, en utilisan...
We develop a grid based numerical approach to solve a filtering problem, using results on optimal qu...
25p.International audienceWe elucidate the asymptotics of the L^s-quantization error induced by a se...
International audienceWe propose a new method based on evolutionary optimization for obtaining an op...
International audienceWe propose a new method based on evolutionary optimization for obtaining an op...
Résumé. Nous construisons un estimateur non-paramétrique des quantiles conditionnels de Y sachant X ...
PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF
30 pagesWe investigate the greedy version of the L^p-optimal vector quantization problem for an R^d-...
We present an introductory survey to optimal vector quantization and its first application...
We present an introductory survey to optimal vector quantization and its first application...
Cette thèse est divisée en quatre parties pouvant être lues indépendamment. Dans ce manuscrit, nous ...
This thesis is concerned with the study of optimal quantization and its applications. We deal with t...
31 pagesInternational audienceLet $P$ be a probability distribution on $\mathbb{R}^d$ (equipped with...
This thesis is concerned with the study of optimal quantization and its applications. We deal with t...
Dans la première partie, nous nous concentrons sur la quantification vectorielle gloutonne. Nous éta...
Nous développons une approche de résolution numérique du filtrage par méthode de grille, en utilisan...
We develop a grid based numerical approach to solve a filtering problem, using results on optimal qu...
25p.International audienceWe elucidate the asymptotics of the L^s-quantization error induced by a se...
International audienceWe propose a new method based on evolutionary optimization for obtaining an op...
International audienceWe propose a new method based on evolutionary optimization for obtaining an op...
Résumé. Nous construisons un estimateur non-paramétrique des quantiles conditionnels de Y sachant X ...
PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF
30 pagesWe investigate the greedy version of the L^p-optimal vector quantization problem for an R^d-...
We present an introductory survey to optimal vector quantization and its first application...
We present an introductory survey to optimal vector quantization and its first application...