Título: Concentration bounds for stochastic approximations
Autores: Frikha, Noufel; Université Denis Diderot
Menozzi, Stéphane; Universite d'Évry Val d'Essonne
Fecha: 2012-01-02
Publicador: Electronic communications in probability
Fuente:
Tipo: Peer-reviewed Article
Tema: Non asymptotic bounds, Euler scheme, Stochastic approximation algorithms, Gaussian concentration
60H35; 65C30; 65C05
Descripción: We obtain non asymptotic concentration bounds for two kinds of stochastic approximations. We first consider the deviations between the expectation of a given function of an Euler like discretization scheme of some diffusion process at a fixed deterministic time and its empirical mean obtained by the Monte Carlo procedure. We then give some estimates concerning the deviation between the value at a given time-step of a stochastic approximation algorithm and its target. Under suitable assumptions both concentration bounds turn out to be Gaussian. The key tool consists in exploiting accurately the concentration properties of the increments of the schemes. Also, no specific non-degeneracy conditions are assumed.An Erratum is available in ECP volume 17 paper number 60.
Idioma: Inglés

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