activity
20092024
most citedA Stochastic forward-backward splitting method for solving monotone inclusions in Hilbert spaces

18 citations · 58 across the 18 of their papers we have counts for

collaborators

21 papers

math.OC2024★ 1 cited

A primal-dual backward reflected forward splitting algorithm for structured monotone inclusions

Vu Cong Bang, Dimitri Papadimitriou, Vu Xuan Nham

We propose a primal-dual backward reflected forward splitting method for solving structured primal-dual monotone inclusion in real Hilbert space. The algorithm allows to use the in…

math.OC2021★ 3 cited

Convergence analysis of the stochastic reflected forward-backward splitting algorithm

Nguyen Van Dung, Bang Cong Vu

We propose and analyze the convergence of a novel stochastic algorithm for solving monotone inclusions that are the sum of a maximal monotone operator and a monotone, Lipschitzian…

math.OC2019

Finding the forward-Douglas-Rachford-forward method

Ernest K. Ryu, Bang Cong Vu

We consider the monotone inclusion problem with a sum of 3 operators, in which 2 are monotone and 1 is monotone-Lipschitz. The classical Douglas--Rachford and Forward-backward-forw…

math.OC2019

A reflected forward-backward splitting method for monotone inclusions involving Lipschitzian operators

Volkan Cevher, Bang Cong Vu

The proximal extrapolated gradient method \cite{Malitsky18a} is an extension of the projected reflected gradient method \cite{Malitsky15}. Both methods were proposed for solving th…

math.OC2019

Inertial Three-Operator Splitting Method and Applications

Volkan Cevher, Bang Cong Vu, Alp Yurtsever

We introduce an inertial variant of the forward-Douglas-Rachford splitting and analyze its convergence. We specify an instance of the proposed method to the three-composite convex…

math.OC2017★ 1 cited

On the linear convergence of the stochastic gradient method with constant step-size

Volkan Cevher, Bang Cong Vu

The strong growth condition (SGC) is known to be a sufficient condition for linear convergence of the stochastic gradient method using a constant step-size (SGM-CS). In this pa…