@techreport{936461e522ff461b908ed4992d63b1cf,
title = "Forward-backward-forward methods with variance reduction for stochastic variational inequalities",
abstract = "We develop a new stochastic algorithm with variance reduction for solving pseudo-monotone stochastic variational inequalities. Our method builds on Tseng's forward-backward-forward (FBF) algorithm, which is known in the deterministic literature to be a valuable alternative to Korpelevich's extragradient method when solving variational inequalities over a convex and closed set governed by pseudo-monotone, Lipschitz continuous operators. The main computational advantage of Tseng's algorithm is that it relies only on a single projection step and two independent queries of a stochastic oracle. Our algorithm incorporates a variance reduction mechanism and leads to almost sure (a.s.) convergence to an optimal solution. To the best of our knowledge, this is the first stochastic look-ahead algorithm achieving this by using only a single projection at each iteration.",
author = "Panayotis Mertikopoulos and Mathias Staudigl and {Radu Ioan Bot} and {Phan Tuo Vong}",
year = "2019",
language = "English",
publisher = "Cornell University - arXiv",
address = "United States",
type = "WorkingPaper",
institution = "Cornell University - arXiv",
}