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20182026
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math.OC2026

Regularized Projection Algorithms for Monotone Inverse Variational Inequalities

Griffin Smith, Zeinab Alizadeh, Afrooz Jalilzadeh

Stochastic inverse variational inequalities (SIVIs) arise in applications in which equilibrium responses are observed under uncertainty, such as inverse road pricing and network eq…

math.OC2026

On the Analysis of Misspecified Variational Inequalities with Nonlinear Constraints

Novel Kumar Dey, Mohammad Mahdi Ahmadi, Erfan Yazdandoost Hamedani +1

In this paper, we study a class of misspecified variational inequalities (VIs) where both the monotone operator and nonlinear convex constraints depend on an unknown parameter lear…

math.OC2025

Distributionally Robust Nash Equilibria via Variational Inequalities

Zeinab Alizadeh, Azadeh Farsi, Afrooz Jalilzadeh

Nash Equilibrium and its robust counterpart, Distributionally Robust Nash Equilibrium (DRNE), are fundamental problems in game theory with applications in economics, engineering, a…

math.OC2025

Semi-infinite Nonconvex Constrained Min-Max Optimization

Cody Melcher, Zeinab Alizadeh, Lindsey Hiett +2

Semi-Infinite Programming (SIP) has emerged as a powerful framework for modeling problems with infinite constraints, however, its theoretical development in the context of nonconve…

math.OC2025

Linear Convergence of a Unified Primal--Dual Algorithm for Convex--Concave Saddle Point Problems with Quadratic Growth

Cody Melcher, Afrooz Jalilzadeh, Erfan Yazdandoost Hamedani

In this paper, we study saddle point (SP) problems, focusing on convex-concave optimization involving functions that satisfy either two-sided quadratic functional growth (QFG) or t…

math.OC2025

Riemannian Inexact Gradient Descent for Quadratic Discrimination

Uday Talwar, Meredith K. Kupinski, Afrooz Jalilzadeh

We propose an inexact optimization algorithm on Riemannian manifolds, motivated by quadratic discrimination tasks in high-dimensional, low-sample-size (HDLSS) imaging settings. In…