We propose an extragradient method with stepsizes bounded away from zero for stochastic
variational inequalities requiring only pseudomonotonicity. We provide convergence and …

We propose a novel stochastic method, namely the stochastic accelerated mirror-prox
(SAMP) method, for solving a class of monotone stochastic variational inequalities (SVI). The …

Uncertainty Quantification (UQ) is an emerging and extremely active research discipline
which aims to quantitatively treat any uncertainty in applied models. The primary objective of …

Variational inequality modeling, analysis and computations are important for many
applications, but much of the subject has been developed in a deterministic setting with no …

In this paper, we propose dynamic sampled stochastic approximated (DS-SA) extragradient
methods for stochastic variational inequalities (SVIs) that are robust with respect to an …

In this paper, we propose a discretization scheme for the two-stage stochastic linear
complementarity problem (LCP) where the underlying random data are continuously …

A solution of two-stage stochastic generalized equations is a pair: a first stage solution which
is independent of realization of the random data and a second stage solution which is a …

We propose a two-stage stochastic variational inequality model to deal with random
variables in variational inequalities, and formulate this model as a two-stage stochastic …

This paper formally introduces and studies a non-cooperative multi-agent game under
uncertainty. The well-known Nash equilibrium is employed as the solution concept of the …

We consider stochastic variational inequalities (VIs) with monotone operators where the
feasible set is an intersection of a large number of convex sets. We propose a stochastic …