Stochastic algorithms are random dynamical systems designed through heuristical methods in order to solve many challenges in optimisation frameworks like those arising in modern statistical analysis. Data are nowadays more and more often represented through complex high-dimensional spaces.This is a motivation for many theoretical, numerical and applied open questions. These algorithms are then privileged basic components for nonparametric statistical methods in the framework for instance of regression function estimation, survival analysis and deconvolution.

This meeting aims at fostering discussions between interested researchers,

With support funding of research federation MIRES et du LMA Poitiers

P.-Y. Louis (LMA Poitiers)

D. Meneveaux (Xlim)

Y. Slaoui (LMA Poitiers)

 organisational support :

J. Attab

B. Brault

N. Echevard

N. Mongin