Minimizing convex quadratics with variable precision Krylov methods

Toint, P. (Speaker)

Activity: Talk or presentation types › Invited talk

Description

Iterative algorithms for the solution of convex quadratic optimization problems are investigated, which exploit inaccurate matrix-vector products. Theoretical bounds on the performance of a Conjugate Gradients method are derived, the necessary quantities occurring in the theoretical bounds estimated and a new practical algorithm derived. Numerical experiments suggest that the new method has significant potential, including in the steadily more important context of multi-precision computations.
Period28 Nov 2019
Held atOxford University, United Kingdom
Degree of RecognitionRegional

Keywords

  • linear algebra
  • optimization
  • inexact computations

Documents & Links

  • 2019_oxford

    File: application/pdf, 780 KB

    Type: Audiovisual

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