4 papers
Stein Variational Gradient Descent dynamics for highly concentrated kernels
José A. Carrillo, Jakub Skrzeczkowski, Jethro Warnett
Stein Variational Gradient Descent (SVGD) is a widely used in practice algorithm for scalable sampling with deterministic particle updates. We study its behavior in the singular li…
Well-posedness and mean-field limit estimate of a consensus-based algorithm for min-max problems
Hui Huang, Jethro Warnett
The recent work arXiv:2407.17373 proposes a derivative-free consensus-based particle method that computes global solutions to nonconvex-nonconcave min-max problems and establishes…
Well-posedness and mean-field limit estimate of a consensus-based algorithm for multiplayer games
Hui Huang, Jethro Warnett
Recently, the paper [12] introduces a derivative-free consensus-based particle method that finds the Nash equilibrium of non-convex multiplayer games, where it proves the global ex…
The Stein-log-Sobolev inequality and the exponential rate of convergence for the continuous Stein variational gradient descent method
José A. Carrillo, Jakub Skrzeczkowski, Jethro Warnett
The Stein Variational Gradient Descent method is a variational inference method in statistics that has recently received a lot of attention. The method provides a deterministic app…