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Computer Science

D-Index
31
Citations
9121
World Ranking
13356
National Ranking
5343

Overview

Meisam Razaviyayn is affiliated with the University of Southern California in the United States and has a research portfolio primarily focused on Computer Science and Engineering. Their contributions span a variety of specialized subfields and are reflected in numerous publications in recognized academic venues.

Razaviyayn's work extensively engages with the following main fields of study:

  • Computer Science
  • Engineering

The subfields they have contributed to include:

  • Artificial Intelligence
  • Computational Mechanics
  • Molecular Biology
  • Statistics and Probability
  • Transportation

The topics of research explored by Razaviyayn cover a broad range of advanced computational and applied themes:

  • Stochastic Gradient Optimization Techniques
  • Sparse and Compressive Sensing Techniques
  • Privacy-Preserving Technologies in Data
  • Adversarial Robustness in Machine Learning
  • Transportation Planning and Optimization
  • Transportation and Mobility Innovations
  • Genomics and Phylogenetic Studies

They have contributed to multiple papers including:

  • Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances, 2020, IEEE Signal Processing Magazine
  • Efficient Search of First-Order Nash Equilibria in Nonconvex-Concave Smooth Min-Max Problems, 2021, SIAM Journal on Optimization
  • A Block Successive Upper-Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization, 2020, Mathematics of Operations Research
  • A DNA Read Alignment Accelerator Based on Computational RAM, 2020, IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
  • Impedimetric Sensing: An Emerging Tool for Combating the COVID-19 Pandemic, 2023, Biosensors

Razaviyayn's frequent collaborators include:

  • Andrew M. Lowy
  • Sina Baharlouei
  • Maged Dessouky
  • Mingyi Hong
  • Dmitrii M. Ostrovskii

The main publication venues where Razaviyayn has contributed include:

  • arXiv (Cornell University)
  • SIAM Journal on Optimization
  • IEEE Transactions on Automatic Control
  • IEEE Signal Processing Magazine
  • Mathematics of Operations Research

Best Publications

  • An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel

    Qingjiang Shi;M. Razaviyayn;Zhi-Quan Luo;Chen He

  • A UNIFIED CONVERGENCE ANALYSIS OF BLOCK SUCCESSIVE MINIMIZATION METHODS FOR NONSMOOTH OPTIMIZATION

    Meisam Razaviyayn;Mingyi Hong;Zhi Quan Luo

  • Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems

    Mingyi Hong;Zhi Quan Luo;Meisam Razaviyayn

  • A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data: With applications in machine learning and signal processing

    Mingyi Hong;Meisam Razaviyayn;Zhi-Quan Luo;Jong-Shi Pang

  • On the Degrees of Freedom Achievable Through Interference Alignment in a MIMO Interference Channel

    Meisam Razaviyayn;Gennady Lyubeznik;Zhi-Quan Luo

  • Successive Convex Approximation: Analysis and Applications

    Meisam Razaviyayn

  • Iteration complexity analysis of block coordinate descent methods

    Mingyi Hong;Xiangfeng Wang;Meisam Razaviyayn;Zhi-Quan Luo

  • Linear transceiver design for interference alignment: Complexity and computation

    Meisam Razaviyayn;Maziar Sanjabi Boroujeni;Zhi-Quan Luo

  • Solving a class of non-convex min-max games using iterative first order methods

    Maher Nouiehed;Maziar Sanjabi;Tianjian Huang;Jason D. Lee

  • Linear Transceiver Design for Interference Alignment: Complexity and Computation

    M. Razaviyayn;M. Sanjabi;Zhi-Quan Luo

  • Computing B-Stationary Points of Nonsmooth DC Programs

    Jong-Shi Pang;Meisam Razaviyayn;Alberth Alvarado

  • Linear transceiver design for a MIMO interfering broadcast channel achieving max–min fairness

    Meisam Razaviyayn;Mingyi Hong;Zhi Quan Luo

  • A Block Successive Upper-Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization

    Mingyi Hong;Tsung Hui Chang;Xiangfeng Wang;Meisam Razaviyayn

  • A Stochastic Successive Minimization Method for Nonsmooth Nonconvex Optimization with Applications to Transceiver Design in Wireless Communication Networks

    Meisam Razaviyayn;Maziar Sanjabi;Zhi-Quan Luo

  • On the convergence and robustness of training GaNs with regularized optimal transport

    Maziar Sanjabi;Jimmy Ba;Meisam Razaviyayn;Jason D. Lee

  • A New Sequential Optimization Procedure and Its Applications to Resource Allocation for Wireless Systems

    Augusto Aubry;Antonio De Maio;Alessio Zappone;Meisam Razaviyayn

  • Optimal Joint Base Station Assignment and Beamforming for Heterogeneous Networks

    Maziar Sanjabi;Meisam Razaviyayn;Zhi-Quan Luo

  • Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances

    Meisam Razaviyayn;Tianjian Huang;Songtao Lu;Maher Nouiehed

  • Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization

    Meisam Razaviyayn;Mingyi Hong;Zhi-Quan Luo;Jong-Shi Pang

  • A stackelberg game approach to distributed spectrum management

    Meisam Razaviyayn;Zhi-Quan Luo;Paul Tseng;Jong-Shi Pang

Frequent Co-Authors

Zhi-Quan Luo
Zhi-Quan Luo Chinese University of Hong Kong, Shenzhen
Mingyi Hong
Mingyi Hong University of Minnesota
Jong-Shi Pang
Jong-Shi Pang University of Southern California
Jason D. Lee
Jason D. Lee Princeton University
David Tse
David Tse Stanford University
Qingjiang Shi
Qingjiang Shi Tongji University
Shiqian Ma
Shiqian Ma Rice University
Tsung-Hui Chang
Tsung-Hui Chang Chinese University of Hong Kong, Shenzhen
Chris H. Kim
Chris H. Kim University of Minnesota
Sachin S. Sapatnekar
Sachin S. Sapatnekar University of Minnesota

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