A Projection-Based Algorithm for Solving Stochastic Inverse Variational Inequality Problems
Optimization and Control
2023-12-08 v2
Abstract
We consider a stochastic Inverse Variational Inequality (IVI) problem defined by a continuous and co-coercive map over a closed and convex set. Motivated by the absence of performance guarantees for stochastic IVI, we present a variance-reduced projection-based gradient method. Our proposed method ensures an almost sure convergence of the generated iterates to the solution, and we establish a convergence rate guarantee. To verify our results, we apply the proposed algorithm to a network equilibrium control problem.
Cite
@article{arxiv.2305.08028,
title = {A Projection-Based Algorithm for Solving Stochastic Inverse Variational Inequality Problems},
author = {Zeinab Alizadeh and Felipe Parra Polanco and Afrooz Jalilzadeh},
journal= {arXiv preprint arXiv:2305.08028},
year = {2023}
}