Farzad Yousefian

Orcid: 0000-0003-2628-741X

According to our database1, Farzad Yousefian authored at least 25 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Randomized Lagrangian stochastic approximation for large-scale constrained stochastic Nash games.
Optim. Lett., March, 2024

2023
An Incremental Gradient Method for Optimization Problems With Variational Inequality Constraints.
IEEE Trans. Autom. Control., December, 2023

Complexity guarantees for an implicit smoothing-enabled method for stochastic MPECs.
Math. Program., April, 2023

A Fish Rheotaxis Mechanism as a Zero-Order Optimization Strategy.
IEEE Access, 2023

Zeroth-Order Methods for Nondifferentiable, Nonconvex, and Hierarchical Federated Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
A Variable Sample-Size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization.
Math. Oper. Res., 2022

2021
A Method with Convergence Rates for Optimization Problems with Variational Inequality Constraints.
SIAM J. Optim., 2021

Bilevel Distributed Optimization in Directed Networks.
Proceedings of the 2021 American Control Conference, 2021

An Incremental Gradient Method for Large-scale Distributed Nonlinearly Constrained Optimization.
Proceedings of the 2021 American Control Conference, 2021

2020
On Stochastic and Deterministic Quasi-Newton Methods for Nonstrongly Convex Optimization: Asymptotic Convergence and Rate Analysis.
SIAM J. Optim., 2020

2019
Self-Tuned Mirror Descent Schemes for Smooth and Nonsmooth High-Dimensional Stochastic Optimization.
IEEE Trans. Autom. Control., 2019

A First-order Method for Monotone Stochastic Variational Inequalities on Semidefinite Matrix Spaces.
Proceedings of the 2019 American Control Conference, 2019

A Randomized Block Coordinate Iterative Regularized Subgradient Method for High-dimensional Ill-posed Convex Optimization.
Proceedings of the 2019 American Control Conference, 2019

An Iterative Regularized Incremental Projected Subgradient Method for a Class of Bilevel Optimization Problems.
Proceedings of the 2019 American Control Conference, 2019

2018
Recent Trends in stochastic Gradient Descent for Machine Learning and Big Data.
Proceedings of the 2018 Winter Simulation Conference, 2018

2017
On smoothing, regularization, and averaging in stochastic approximation methods for stochastic variational inequality problems.
Math. Program., 2017

A smoothing stochastic quasi-newton method for non-lipschitzian stochastic optimization problems.
Proceedings of the 2017 Winter Simulation Conference, 2017

2016
Self-Tuned Stochastic Approximation Schemes for Non-Lipschitzian Stochastic Multi-User Optimization and Nash Games.
IEEE Trans. Autom. Control., 2016

Stochastic quasi-Newton methods for non-strongly convex problems: Convergence and rate analysis.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2014
Optimal robust smoothing extragradient algorithms for stochastic variational inequality problems.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2013
A regularized smoothing stochastic approximation (RSSA) algorithm for stochastic variational inequality problems.
Proceedings of the Winter Simulations Conference: Simulation Making Decisions in a Complex World, 2013

A distributed adaptive steplength stochastic approximation method for monotone stochastic Nash Games.
Proceedings of the American Control Conference, 2013

2012
On stochastic gradient and subgradient methods with adaptive steplength sequences.
Autom., 2012

2011
A regularized adaptive steplength stochastic approximation scheme for monotone stochastic variational inequalities.
Proceedings of the Winter Simulation Conference 2011, 2011

2010
Convex nondifferentiable stochastic optimization: A local randomized smoothing technique.
Proceedings of the American Control Conference, 2010


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