88 citations · 487 across the 78 of their papers we have counts for
4 papers · 2 filters
Second order quantitative bounds for unadjusted generalized Hamiltonian Monte Carlo
Evan Camrud, Alain Durmus, Pierre Monmarché +1
This paper provides a convergence analysis for generalized Hamiltonian Monte Carlo samplers, a family of Markov Chain Monte Carlo methods based on leapfrog integration of Hamiltoni…
Non-asymptotic convergence bounds for Sinkhorn iterates and their gradients: a coupling approach
Giacomo Greco, Maxence Noble, Giovanni Conforti +1
Computational optimal transport (OT) has recently emerged as a powerful framework with applications in various fields. In this paper we focus on a relaxation of the original OT pro…
Quantitative contraction rates for Sinkhorn's algorithm: beyond bounded costs and compact marginals
Giovanni Conforti, Alain Durmus, Giacomo Greco
We show non-asymptotic exponential convergence of Sinkhorn iterates to the Schrödinger potentials, solutions of the quadratic Entropic Optimal Transport problem on .…
Rosenthal-type inequalities for linear statistics of Markov chains
Alain Durmus, Eric Moulines, Alexey Naumov +2
In this paper, we establish novel concentration inequalities for additive functionals of geometrically ergodic Markov chains similar to Rosenthal inequalities for sums of independe…