6 citations · 14 across the 4 of their papers we have counts for
4 papers · 1 filter
A Non-Asymptotic Analysis for Stein Variational Gradient Descent
Anna Korba, Adil Salim, Michael Arbel +2
We study the Stein Variational Gradient Descent (SVGD) algorithm, which optimises a set of particles to approximate a target probability distribution on $\mathbb{…
Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm
Adil Salim, Peter Richtárik
We consider the task of sampling with respect to a log concave probability distribution. The potential of the target distribution is assumed to be composite, \textit{i.e.}, written…
Maximum Mean Discrepancy Gradient Flow
Michael Arbel, Anna Korba, Adil Salim +1
We construct a Wasserstein gradient flow of the maximum mean discrepancy (MMD) and study its convergence properties. The MMD is an integral probability metric defined for a reprodu…
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates
Adil Salim, Dmitry Kovalev, Peter Richtárik
We propose a new algorithm---Stochastic Proximal Langevin Algorithm (SPLA)---for sampling from a log concave distribution. Our method is a generalization of the Langevin algorithm…