25 citations · 31 across the 23 of their papers we have counts for
27 papers
A Bilevel Market Equilibrium Model for Natural Gas Pipeline Network Operations: Convex Relaxations and Single-level Reformulations
Novel Kumar Dey, Afrooz Jalilzadeh, Erfan Yazdandoost Hamedani +2
We propose an integrated market equilibrium model for determining the spot market prices and flow rates in a natural gas pipeline network. The traditional approach solves the marke…
Residual Feedback for Transformed-State Equilibrium Seeking via General Variational Inequalities
Griffin Smith, Afrooz Jalilzadeh
Motivated by networked systems in which equilibrium conditions apply to a regulated state rather than directly to the decision variable, we study transformed-state general variatio…
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…
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…
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…
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…
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…
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…
Variance-reduction for Variational Inequality Problems with Bregman Distance Function
Zeinab Alizadeh, Erfan Yazdandoost Hamedani, Afrooz Jalilzadeh
In this paper, we address variational inequalities (VI) with a finite-sum structure. We introduce a novel single-loop stochastic variance-reduced algorithm, incorporating the Bregm…
Convergence Analysis of Non-Strongly-Monotone Stochastic Quasi-Variational Inequalities
Zeinab Alizadeh, Afrooz Jalilzadeh
While Variational Inequality (VI) is a well-established mathematical framework that subsumes Nash equilibrium and saddle-point problems, less is known about its extension, Quasi-Va…
Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems
Morteza Boroun, Erfan Yazdandoost Hamedani, Afrooz Jalilzadeh
In this paper, we investigate a class of constrained saddle point (SP) problems where the objective function is nonconvex-concave and smooth. This class of problems has wide applic…
A Projection-Based Algorithm for Solving Stochastic Inverse Variational Inequality Problems
Zeinab Alizadeh, Felipe Parra Polanco, Afrooz Jalilzadeh
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 performa…
Randomized Lagrangian Stochastic Approximation for Large-Scale Constrained Stochastic Nash Games
Zeinab Alizadeh, Afrooz Jalilzadeh, Farzad Yousefian
In this paper, we consider stochastic monotone Nash games where each player's strategy set is characterized by possibly a large number of explicit convex constraint inequalities. N…
Accelerated Primal-dual Scheme for a Class of Stochastic Nonconvex-concave Saddle Point Problems
Morteza Boroun, Zeinab Alizadeh, Afrooz Jalilzadeh
Stochastic nonconvex-concave min-max saddle point problems appear in many machine learning and control problems including distributionally robust optimization, generative adversari…
An Accelerated Asynchronous Distributed Method for Convex Constrained Optimization Problems
Nazanin Abolfazli, Afrooz Jalilzadeh, Erfan Yazdandoost Hamedani
We consider a class of multi-agent cooperative consensus optimization problems with local nonlinear convex constraints where only those agents connected by an edge can directly com…
An Inexact Variance-Reduced Method For Stochastic Quasi-Variational Inequality Problems With An Application In Healthcare
Zeinab Alizadeh, Brianna M. Otero, Afrooz Jalilzadeh
This paper is focused on a stochastic quasi-variational inequality (SQVI) problem with a continuous and strongly-monotone mapping over a closed and convex set where the projection…
Stochastic Approximation for Estimating the Price of Stability in Stochastic Nash Games
Afrooz Jalilzadeh, Farzad Yousefian, Mohammadjavad Ebrahimi
The goal in this paper is to approximate the Price of Stability (PoS) in stochastic Nash games using stochastic approximation (SA) schemes. PoS is amongst the most popular metrics…
Inexact-Proximal Accelerated Gradient Method for Stochastic Nonconvex Constrained Optimization Problems
Morteza Boroun, Afrooz Jalilzadeh
Stochastic nonconvex optimization problems with nonlinear constraints have a broad range of applications in intelligent transportation, cyber-security, and smart grids. In this pap…
A Stochastic Variance-reduced Accelerated Primal-dual Method for Finite-sum Saddle-point Problems
Erfan Yazdandoost Hamedani, Afrooz Jalilzadeh
In this paper, we propose a variance-reduced primal-dual algorithm with Bregman distance for solving convex-concave saddle-point problems with finite-sum structure and nonbilinear…
Primal-Dual Incremental Gradient Method for Nonsmooth and Convex Optimization Problems
Afrooz Jalilzadeh
In this paper, we consider a nonsmooth convex finite-sum problem with a conic constraint. To overcome the challenge of projecting onto the constraint set and computing the full (su…
A Proximal-Point Algorithm with Variable Sample-sizes (PPAWSS) for Monotone Stochastic Variational Inequality Problems
Afrooz Jalilzadeh, Uday V. Shanbhag
We consider a stochastic variational inequality (SVI) problem with a continuous and monotone mapping over a closed and convex set. In strongly monotone regimes, we present a variab…
A Randomized Block-Coordinate Primal-Dual Method for Large-scale Stochastic Saddle Point Problems
Erfan Yazdandoost Hamedani, Afrooz Jalilzadeh, Necdet Serhat Aybat
We consider (stochastic) convex-concave saddle point (SP) problems with high-dimensional decision variables, arising in various applications including machine learning problems. To…
Randomized Primal-Dual Methods with Adaptive Step Sizes
E. Yazdandoost Hamedani, A. Jalilzadeh, N. S. Aybat
In this paper we propose a class of randomized primal-dual methods to contend with large-scale saddle point problems defined by a convex-concave function $\mathcal{L}(\mathbf{x},y)…
A Variable Sample-size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization
Afrooz Jalilzadeh, Angelia Nedich, Uday V. Shanbhag +1
Classical theory for quasi-Newton schemes has focused on smooth deterministic unconstrained optimization while recent forays into stochastic convex optimization have largely reside…