105 citations · 271 across the 24 of their papers we have counts for
4 papers · 1 filter
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization
Dmitry Kovalev, Adil Salim, Peter Richtárik
We consider the task of decentralized minimization of the sum of smooth strongly convex functions stored across the nodes of a network. For this problem, lower bounds on the number…
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…
Dualize, Split, Randomize: Toward Fast Nonsmooth Optimization Algorithms
Adil Salim, Laurent Condat, Konstantin Mishchenko +1
We consider minimizing the sum of three convex functions, where the first one F is smooth, the second one is nonsmooth and proximable and the third one is the composition of a nons…