6 citations · 14 across the 4 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 Fully Stochastic Primal-Dual Algorithm
Pascal Bianchi, Walid Hachem, Adil Salim
A new stochastic primal--dual algorithm for solving a composite optimization problem is proposed. It is assumed that all the functions/operators that enter the optimization problem…
A Constant Step Stochastic Douglas-Rachford Algorithm with Application to Non Separable Regularizations
Adil Salim, Pascal Bianchi, Walid Hachem
The Douglas Rachford algorithm is an algorithm that converges to a minimizer of a sum of two convex functions. The algorithm consists in fixed point iterations involving computatio…
Snake: a Stochastic Proximal Gradient Algorithm for Regularized Problems over Large Graphs
Adil Salim, Pascal Bianchi, Walid Hachem
A regularized optimization problem over a large unstructured graph is studied, where the regularization term is tied to the graph geometry. Typical regularization examples include…