90 citations · 403 across the 37 of their papers we have counts for
5 papers · 1 filter
Success and Failure of Adaptation-Diffusion Algorithms for Consensus in Multi-Agent Networks
Gemma Morral, Pascal Bianchi, Gersende Fort
This paper investigates the problem of distributed stochastic approximation in multi-agent systems. The algorithm under study consists of two steps: a local stochastic approximatio…
Self-Healing Umbrella Sampling: Convergence and efficiency
G. Fort, B. Jourdain, T. Lelievre +1
The Self-Healing Umbrella Sampling (SHUS) algorithm is an adaptive biasing algorithm which has been proposed to efficiently sample a multimodal probability measure. We show that th…
Convergence of Markovian Stochastic Approximation with discontinuous dynamics
Gersende Fort, Eric Moulines, Amandine Schreck +1
This paper is devoted to the convergence analysis of stochastic approximation algorithms of the form where is…
Subgeometric rates of convergence in Wasserstein distance for Markov chains
Alain Durmus, Gersende Fort, Eric Moulines
In this paper, we provide sufficient conditions for the existence of the invariant distribution and for subgeometric rates of convergence in Wasserstein distance for general state-…
On perturbed proximal gradient algorithms
Yves F. Atchade, Gersende Fort, Eric Moulines
We study a version of the proximal gradient algorithm for which the gradient is intractable and is approximated by Monte Carlo methods (and in particular Markov Chain Monte Carlo).…