Inicio

 

Méthodes probabilistes appliquées aux très grands graphes

Informations pratiques


Discipline :

Informatique

Niveau :

Master 2

Semestre :

S3

Crédits ECTS :

3

Volume Horaire :

20h Cours

Responsable :

Stéphan Thomassé

Ecole Normale Supérieure de Lyon, Laboratoire de Physique

Intervenants :

Stéphan Thomassé

Louis Esperet

La Formation

 

Dealing with large (real life) graphs leads to several problems among which one can highlight two major questions: How to generate them? and How to make computations on them? These two directions have a common feature in the sense that one cannot access the full graph, but only parts of it. This refines our approach into : How to generate a graph under some constraints (usually local ones like degree, density of triangles, etc)? and How to compute properties of the graph under statistical knowledge? These question are far reaching, and the objective of this course is to introduce some (usually probabilistic) tools to this purpose.

Plus d'information :  http://oc.inpg.fr/esperet/cours/cr17.html

 

Pré-requis

Introduction to Computer Science

Modalité de l'examen

Devoirs personnels et écrit final

Mots-clés

-