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Dr. Yazdandoost Hamedani is an Assistant Professor at the University of Arizona, Department of Systems and Industrial Engineering. He received his Ph.D. in Industrial Engineering and Operations Research from The Pennsylvania State University. Prior to that, he was a Research Intern at the Department of Mathematics, Penn State University. He received his B.Sc. degree in Mathematics and Applications from The University of Tehran, Tehran, Iran. His research interests include distributed optimization, saddle point problems, bilevel optimization, machine learning, and data science. His research focuses on developing and analyzing algorithms for solving convex and non-convex large-scale optimization problems in machine learning and data science problems.

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Courses
  • NO
    Nonlinear Optimization

  • PMOR
    Probabilistic Models in Operations Research

  • EMI
    Engineering Management I

Grants
  • Funding agency logo
    Collaborative Research: Computationally Efficient Algorithms for Large-scale Bilevel Optimization Problems

    Principal Investigator (PI)

    2021

    $224.4K
    Active
Publications (18)
Recent
  • a href= https://scholar.google.com/citations?view_op=view_citation hl=en user=13CgvOEAAAAJ sortby=pubdate citation_for_view=13CgvOEAAAAJ:3fE2CSJIrl8C An Accelerated Asynchronous Distributed Method for Convex Constrained Optimization Problems /a

    2023

  • An Accelerated Asynchronous Distributed Method for Convex Constrained Optimization Problems

    2023

  • span style= font-size:10pt; Randomized Primal-Dual Methods with Adaptive Step Sizes /span span style= font-size:medium; /span

    2023

  • Randomized Primal-Dual Methods with Adaptive Step Sizes

    2023

  • A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem

    2022

  • A Stochastic Variance-reduced Accelerated Primal-dual Method for Finite-sum Saddle-point Problems

    2020

  • Primal-Dual Methods for Saddle-Point Problems with Applications to Decentralized Constrained Convex Optimization

    2020

  • A decentralized primal-dual method for constrained minimization of a strongly convex function

    2019

  • A distributed ADMM-like method for resource sharing over time-varying networks

    2019

  • A Doubly-Randomized Block-Coordinate Primal-Dual Method for Large-scale Saddle Point Problems

    2019

  • Iteration complexity of randomized primal-dual methods for convex-concave saddle point problems

    2018

  • A primal-dual algorithm for general convex-concave saddle point problems

    2018

  • Multi-agent constrained optimization of a strongly convex function

    2017

  • Multi-agent constrained optimization of a strongly convex function over time-varying directed networks

    2017

  • A primal-dual method for conic constrained distributed optimization problems

    2016

  • Distributed primal-dual method for multi-agent sharing problem with conic constraints

    2016

  • Inverse Quadratic Transportation Problem

    2014

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