Ming Yan
Associate Professor, Department of Mathematics
Location: 1514 Engineering Bldg
Phone: 517-432-0401
Email: myan@msu.edu
Website: http://www.math.msu.edu/~myan
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Bio
Ming Yan's research lies on the intersection of parallel and distributed algorithms, signal and image processing, and inverse problems. He is particularly interested in developing optimization methods and their applications in sparse recovery and regularized inverse problems, variational methods for image processing, and parallel and distributed algorithms for solving big data problems. Currently, I am working on developing synchronous/asynchronous parallel optimization algorithms for large scale problems.
Selected Publications
- M. Yan, Restoration of images corrupted by impulse noise and mixed Gaussian impulse noise using blind inpainting, SIAM Journal on Imaging Sciences, 6 (2013), 1227-1245. View Publication
- Z. Peng, Y. Xu, M. Yan, and W. Yin, ARock: an algorithmic framework for asynchronous parallel coordinate updates, SIAM Journal on Scientific Computing, 38 (2016), A2851-A2879. View Publication
- M. Yan and W. Yin, Self equivalence of the alternating direction method of multipliers, in R. Glowinski, S. Osher, and W. Yin (Eds.), Splitting Methods in Communication and Imaging, Science and Engineering (2017), New York, Springer, 165-194. View Publication
- H. Tang, X. Lian, M. Yan, C. Zhang and J. Liu, D2: Decentralized training over decentralized data, In: Proceeding of International Conference on Machine Learning 2018, PMLR 80 (2018), 4848-4856. View Publication
- Z. Li, W. Shi, and M. Yan, A decentralized proximal-gradient method with network independent step- sizes and separated convergence rates, IEEE Transactions on Signal Processing, 67 (2019), 4494–4506. View Publication