Qiang Ye

Research Interests:
applied and computational mathematics
Education

Ph.D., University of Calgary, 1989
M.Sc, Chinese Academy of Sciences, 1986
B.Sc., University of Science and Technology of China, 1983

Research

My current research work is focused on the following computational problems. 

  • Deep Learning
  • Preocnditioned Krylov subspace methods for computing eigenvalues of large matrices.
  • High relateive accuracy algorithms for computing eigenvalues and exponentials of matrices

 

 

Selected Publications:

Xue, Jungong; Ye, Qiang Computing exponentials of essentially non-negative matrices entrywise to high relative accuracy. Math. Comp. 82 (2013), no. 283, 1577–1596.

Ye, Qiang Error bounds for the Lanczos methods for approximating matrix exponentials. SIAM J. Numer. Anal. 51 (2013), no. 1, 68–87.

Ye, Qiang; Zhi, Weifeng Analysis of alignment algorithms with mixed dimensions for dimensionality reduction. Numer. Linear Algebra Appl. 20 (2013), no. 2, 369–384.

Ye, Qiang; Zhang, Ping Inexact inverse subspace iteration for generalized eigenvalue problems. Linear Algebra Appl. 434 (2011), no. 7, 1697–1715.

Quillen, Patrick; Ye, Qiang A block inverse-free preconditioned Krylov subspace method for symmetric generalized eigenvalue problems. J. Comput. Appl. Math. 233 (2010), no. 5, 1298–1313.
 
Ye, Qiang Relative perturbation bounds for eigenvalues of symmetric positive definite diagonally dominant matrices. SIAM J. Matrix Anal. Appl. 31 (2009), no. 1, 11–17.