Ming Zhou

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Dr. Ming Zhou
Universität Rostock
Institut für Mathematik
Ulmenstraße 69, Haus 3
18057 Rostock, Germany

Room: 429
Phone: +49 / 381 498 6644
email: ming.zhou@uni-rostock.de

Sprechzeiten

• Dienstag 11:00 - 13:00 Uhr
• Mittwoch 11:00 - 12:00 Uhr
• Donnerstag 13:00 - 14:00 Uhr

Lehrveranstaltungen

siehe lsf.uni-rostock.de

Research interests

• Numerical linear algebra
• Eigenvalue problems
• Adaptive finite elements

Papers

• M. Zhou, K. Neymeyr,
  Cluster robust estimates for block gradient-type eigensolvers.
  
Math. Comp. 88 (2019), 2737-2765. https://doi.org/10.1090/mcom/3446.
• J. Kohler, H. Daneshmand, A. Lucchi, T. Hofmann, M. Zhou, K. Neymeyr,
  Exponential convergence rates for Batch Normalization: The power of length-direction decoupling in non-convex optimization.
  
Proceedings of Machine Learning Research 89 (2019), 806-815.
• M. Zhou,
  Convergence estimates of nonrestarted and restarted block-Lanczos methods.
  
Numer. Linear Algebra Appl. 25 (2018), e2182. https://doi.org/10.1002/nla.2182.
• M. Zhou, K. Neymeyr,
  Sharp Ritz value estimates for restarted Krylov subspace iterations.
  
Electron. Trans. Numer. Anal. 46 (2017), 424-446.
• M.E. Argentati, A.V. Knyazev, K. Neymeyr, E.E. Ovtchinnikov, M. Zhou,
  Convergence theory for preconditioned eigenvalue solvers in a nutshell.
  
Foundations of Computational Mathematics 17 (2017), 713-727.
Paper in arXiv library.   DOI: 10.1007/s10208-015-9297-1.
• K. Neymeyr, M. Zhou,
  Convergence analysis of restarted Krylov subspace eigensolvers.
  
SIAM J. Matrix Anal. & Appl. 37 (2016), 955-975.
DOI:10.1137/16M1056481.
• M. Zhou, K. Neymeyr,
  Users' guide to the AMP Eigensolver (Adaptive Multigrid Preconditioned Eigensolver).
  
Version 1.0, 2014.
• K. Neymeyr, M. Zhou,
  The block preconditioned steepest descent iteration for elliptic operator eigenvalue problems.
  
Electron. Trans. Numer. Anal. 41 (2014), 93-108.
• K. Neymeyr, M. Zhou,
  Iterative minimization of the Rayleigh quotient by block steepest descent iterations.
  
Numer. Linear Algebra Appl. 21 (2014), 604-617.
• K. Neymeyr, E. Ovtchinnikov, M. Zhou,
  Convergence analysis of gradient iterations for the symmetric eigenvalue problem.
  
SIAM J. Matrix Anal. & Appl. 32 (2011), 443-456.
• M. Zhou,
  On the convergence theory of preconditioned subspace iterations for eigenvalue problems.
  
(Proceeding GAMM 2010) Proc. Appl. Math. Mech. 10 (2010), 553-554.

Software

Adaptive Multigrid Preconditioned Eigensolver: A software for the computation of the smallest eigenvalues and the associated eigenfunctions of a self-adjoint and elliptic partial differential operator in 2D domains.