4 citations · 4 across the 2 of their papers we have counts for
2 papers
math.OC2022
Convergence Error Analysis of Reflected Gradient Langevin Dynamics for Globally Optimizing Non-Convex Constrained Problems
Kanji Sato, Akiko Takeda, Reiichiro Kawai +1
Gradient Langevin dynamics and a variety of its variants have attracted increasing attention owing to their convergence towards the global optimal solution, initially in the uncons…
math.PR2020★ 4 cited
Dimension-free convergence rates for gradient Langevin dynamics in RKHS
Boris Muzellec, Kanji Sato, Mathurin Massias +1
Gradient Langevin dynamics (GLD) and stochastic GLD (SGLD) have attracted considerable attention lately, as a way to provide convergence guarantees in a non-convex setting. However…