@article{cb2d8cdf4474494e98f0d9b2a9675d00,
title = "Mini-batch forward-backward-forward methods for solving stochastic variational inequalities",
abstract = "We develop a new stochastic algorithm for solving pseudomonotone stochastic variational inequalities. Our method builds on Tseng{\textquoteright}s forward-backward-forward algorithm, which is known in the deterministic literature to be a valuable alternative to Korpelevich{\textquoteright}s extragradient method when solving variational inequalities over a convex and closed set governed by pseudomonotone Lipschitz continuous operators. The main computational advantage of Tseng{\textquoteright}s algorithm is that it relies only on a single projection step and two independent queries of a stochastic oracle. Our algorithm incorporates a minibatch sampling mechanism and leads to almost sure 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 = "Radu Bot and Panayotis Mertikopoulos and Mathias Staudigl and Vuong, {Phan Tuo}",
note = "Funding Information: R. I. Bo{\c t} and P. T. Vuong acknowledge support from the Austrian Science Fund [Project I2419-N32: “Employing Recent Outcomes in Proximal Theory Outside the Comfort Zone”]. P. M. is grateful for financial support from the French National Research Agency (ANR) in the framework of the Investissements d{\textquoteright}avenir program [ANR-15-IDEX-02], the LabEx PERSYVAL [ANR-11-LABX-0025-01], and MIAI@Grenoble Alpes [ANR-19-P3IA-0003]. M. Staudigl and P. Mertikopoulos have been sponsored by the COST Action CA16228 “European Network for Game Theory.”. Publisher Copyright: {\textcopyright} 2021 The Author(s).",
year = "2021",
month = feb,
day = "25",
doi = "10.1287/stsy.2019.0064",
language = "English",
volume = "11",
pages = "112--139",
journal = "Stochastic Systems",
issn = "1946-5238",
publisher = "INFORMS",
number = "2",
}