ROUSSEL Olivier

دكـتور
وحـدة : APR
تاريـخ المـغادرة : 30/09/2012
https://lip6.fr/Olivier.Roussel

رئاسـة البـحث : Michèle SORIA

Générateur aléatoire de strutures ordonnées par le modèle de Boltzmann

Uniform random generation is a central issue in combinatorics. Indeed, random sampling is virtually connected to all parts of combinatorics, whether to exact or asymptotic enumeration, or to the experimental verification of conjectures. Various methods have been developed in order to efficiently solve that issue. Boltzmann model is among them. This method, relaxing some constraints about the size of the object being currently generated, ensures a linear complexity in many actual cases, and can easily be automatized for various combinatorial classes. This thesis aims at enlarging the set of such admissible classes, while keeping the nice properties of linear complexity and ease of automation. The first part is devoted to the presentation of the Boltzmann model and existing Boltzmann samplers, and the study of their properties and mathematical foundations. In the second part, we introduce our idea of biasing those samplers in order to enlarge their range of validity. Firstly, we present a general extension, and then specialize it to several combinatorial operations such as the derivation, the shuffle product or the unpointing operation. Finally, we present a uniform random sampler for the Hadamard product. We highlight our algorithms through this thesis with examples and experimental results, illustrating the efficiency of our methods.

مناقـشـة مـذكـرة : 25/09/2012

أعـضاء لجنة المناقـشة :

Philippe Duchon
Conrado Martínez
Olivier Bodini
Christoph Dürr
Cyril Nicaud
Konstantinos Panagiotou
Bruno Salvy
Michèle Soria

تاريـخ المـغادرة : 30/09/2012

1 دكـتور 2018

إصدارات 2009-2022

Mentions légales
خـريـطـة المـوقـع