Ming Yan (严明)

Ming Yan (严明)

Michigan State University

H-index: 26

North America-United States

About Ming Yan (严明)

Ming Yan (严明), With an exceptional h-index of 26 and a recent h-index of 22 (since 2020), a distinguished researcher at Michigan State University, specializes in the field of Optimization, Numerical Analysis, Compressive Sensing, Image Processing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Provably accelerated decentralized gradient method over unbalanced directed graphs

Fast Robust Principle Component Analysis Using Gauss-Newton Iterations

Accelerated sparse recovery via gradient descent with nonlinear conjugate gradient momentum

Optimal gradient tracking for decentralized optimization

FedRolex: Model-heterogeneous federated learning with rolling sub-model extraction

On the improved conditions for some primal-dual algorithms

Communication-efficient topologies for decentralized learning with O(1) consensus rate

Hessian informed mirror descent

Ming Yan (严明) Information

University

Position

Assistant Professor

Citations(all)

2966

Citations(since 2020)

2154

Cited By

1583

hIndex(all)

26

hIndex(since 2020)

22

i10Index(all)

46

i10Index(since 2020)

38

Email

University Profile Page

Google Scholar

Ming Yan (严明) Skills & Research Interests

Optimization

Numerical Analysis

Compressive Sensing

Image Processing

Top articles of Ming Yan (严明)

Title

Journal

Author(s)

Publication Date

Provably accelerated decentralized gradient method over unbalanced directed graphs

SIAM Journal on Optimization

Zhuoqing Song

Lei Shi

Shi Pu

Ming Yan

2024

Fast Robust Principle Component Analysis Using Gauss-Newton Iterations

William Chettleburgh

Zhishen Huang

Ming Yan

2023/6/4

Accelerated sparse recovery via gradient descent with nonlinear conjugate gradient momentum

Journal of Scientific Computing

Mengqi Hu

Yifei Lou

Bao Wang

Ming Yan

Xiu Yang

...

2023/4

Optimal gradient tracking for decentralized optimization

Mathematical Programming

Zhuoqing Song

Lei Shi

Shi Pu

Ming Yan

2023

FedRolex: Model-heterogeneous federated learning with rolling sub-model extraction

Samiul Alam

Luyang Liu

Ming Yan

Mi Zhang

2022/11

On the improved conditions for some primal-dual algorithms

arXiv preprint arXiv:2201.00139

Yao Li

Ming Yan

2022/1/1

Communication-efficient topologies for decentralized learning with O(1) consensus rate

Zhuoqing Song

Weijian Li

Kexin Jin

Lei Shi

Ming Yan

...

2022/10/14

Hessian informed mirror descent

Journal of Scientific Computing

Li Wang

Ming Yan

2022/9

Compressed gradient tracking for decentralized optimization over general directed networks

IEEE Transactions on Signal Processing

Zhuoqing Song

Lei Shi

Shi Pu

Ming Yan

2022/3/17

Phase retrieval from incomplete data via weighted nuclear norm minimization

Pattern Recognition

Zhi Li

Ming Yan

Tieyong Zeng

Guixu Zhang

2022/1/14

Linear convergent decentralized optimization with compression

ICLR 2021 (International Conference on Learning Representations)

Xiaorui Liu

Yao Li

Rongrong Wang

Jiliang Tang

Ming Yan

2020/7/1

Elastic graph neural networks

Xiaorui Liu*

Wei Jin*

Yao Ma

Yaxin Li

Hua Liu

...

2021/7/1

Decentralized frequency alignment for collaborative beamforming in distributed phased arrays

IEEE Transactions on Wireless Communications

Hassna Ouassal

Ming Yan

Jeffrey A Nanzer

2021

Image enhancement in active incoherent millimeter-wave imaging

Stavros Vakalis

Daniel Chen

Ming Yan

Jeffrey A Nanzer

2021/4/12

ErrorCompensatedX: error compensation for variance reduced algorithms

Advances in Neural Information Processing Systems

Hanlin Tang

Yao Li

Ji Liu

Ming Yan

2021/12/6

Surface-aware blind image deblurring

IEEE transactions on pattern analysis and machine intelligence

Jun Liu

Ming Yan

Tieyong Zeng

2019/9/16

New convergence analysis of a primal-dual algorithm with large stepsizes

Advances in Computational Mathematics

Zhi Li

Ming Yan

2021/2

Mercury: efficient on-device distributed DNN training via stochastic importance sampling

Xiao Zeng

Ming Yan

Mi Zhang

2021/11/15

On linear convergence of two decentralized algorithms

Journal of Optimization Theory and Applications

Yao Li

Ming Yan

2021

Fast algorithms for robust principal component analysis with an upper bound on the rank

Inverse Problems and Imaging

Ningyu Sha

Lei Shi

Ming Yan

2021

See List of Professors in Ming Yan (严明) University(Michigan State University)

Co-Authors

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