4 papers · 1 filter
Toward genuine efficiency and cluster robustness of preconditioned CG-like eigensolvers
Ming Zhou, Klaus Neymeyr
The performance of eigenvalue problem solvers (eigensolvers) depends on various factors such as preconditioning and eigenvalue distribution. Developing stable and rapidly convergin…
Angle-free cluster robust Ritz value bounds for restarted block eigensolvers
Ming Zhou, Andrew V. Knyazev, Klaus Neymeyr
Convergence rates of block iterations for solving eigenvalue problems typically measure errors of Ritz values approximating eigenvalues. The errors of the Ritz values are commonly…
Convergence analysis of a block preconditioned steepest descent eigensolver with implicit deflation
Ming Zhou, Zhaojun Bai, Yunfeng Cai +1
Gradient-type iterative methods for solving Hermitian eigenvalue problems can be accelerated by using preconditioning and deflation techniques. A preconditioned steepest descent it…
Majorization-type cluster robust bounds for block filters and eigensolvers
M. Zhou, M. E. Argentati, A. V. Knyazev +1
Convergence analysis of block iterative solvers for Hermitian eigenvalue problems and the closely related research on properties of matrix-based signal filters are challenging, and…