Description
Date depot: 19 mars 2021
Titre: Efficient Algorithms for Discrepancy Subset Selection
Directrice de thèse:
Carola DOERR (LIP6)
Encadrant :
Luís PAQUETE (Universidade de Coimbra)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Algorithmique, combinatoire
Resumé: Star discrepancy measure how regularly a set of points is distributed in a given space. Point sets of low star discrepancy have several important applications including Quasi-Monte Carlo integration, financial mathematics, optimization, design of experiments, and many more.
The main goal of this PhD project is the design and the analysis of efficient algorithms to address the following discrepancy subset selection problem: for a given set of points X={x1,…,xn} in [0,1]^d and a given target size m<n, select m points which minimize the star discrepancy.
The PhD student will be supervised by Carola Doerr from LIP6, Sorbonne Université and Luís Paquete from the University of Coimbra in Portugal.
Doctorant.e: Clement François Pierre Emmerich