4 citations · 6 across the 3 of their papers we have counts for
3 papers
Optimal Scaling Results for Moreau-Yosida Metropolis-adjusted Langevin Algorithms
Francesca R. Crucinio, Alain Durmus, Pablo Jiménez +1
We consider a recently proposed class of MCMC methods which uses proximity maps instead of gradients to build proposal mechanisms which can be employed for both differentiable and…
On Riemannian Stochastic Approximation Schemes with Fixed Step-Size
Alain Durmus, Pablo Jiménez, Éric Moulines +1
This paper studies fixed step-size stochastic approximation (SA) schemes, including stochastic gradient schemes, in a Riemannian framework. It is motivated by several applications,…
Convergence Analysis of Riemannian Stochastic Approximation Schemes
Alain Durmus, Pablo Jiménez, Éric Moulines +2
This paper analyzes the convergence for a large class of Riemannian stochastic approximation (SA) schemes, which aim at tackling stochastic optimization problems. In particular, th…