5 citations · 5 across the 9 of their papers we have counts for
4 papers · 1 filter
Error estimates for tamed Euler and Randomized Euler schemes for SDEs with locally Lipschitz drift with applications to non-logconcave sampling and optimization
Iosif Lytras, Angelos Ntousis
In this paper, we study the numerical discretization of stochastic differential equations with locally Lipschitz, super-linearly growing drift, and the resulting implications for s…
Contractive kinetic Langevin samplers beyond global Lipschitz continuity
Iosif Lytras, Panayotis Mertikopoulos
In this paper, we examine the problem of sampling from log-concave distributions with (possibly) superlinear gradient growth under kinetic (underdamped) Langevin algorithms. Using…
Taming under isoperimetry
Iosif Lytras, Sotirios Sabanis
In this article we propose a novel taming Langevin-based scheme called to sample from distributions with superlinearly growing log-gradient which also satisfy a Lo…
Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity -- the Strongly Convex Case
Tim Johnston, Iosif Lytras, Sotirios Sabanis
In this article we consider sampling from log concave distributions in Hamiltonian setting, without assuming that the objective gradient is globally Lipschitz. We propose two algor…