Link prediction in random graphs

Mercredi, 3. février 2021 - 11:00 - 12:00
Orateur: 

Quentin Duchemin

Résumé: 

Nowadays, random graph models are widely used to extract relevant information on complex systems. One task of particular interest is to infer connections in networks where we only observe a partial amount of all possible links. In this talk, I will present one random graph model that allows to tackle such problems in a high dimensional setting. The talk is designed to be accessible to every PhD students coming from any field of maths. The purpose is mainly to introduce some key concepts/questions/tools of high dimensional statistics and optimization.