Activities per year
Abstract
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 and a Full-Orthormalization methods are derived, the necessary quantities occurring in the theoretical bounds estimated and new practical algorithms derived. Numerical experiments suggest that the new methods have significant potential, including in the steadily more important context of multi-precision computations.
Original language | English |
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Pages (from-to) | e2337 |
Number of pages | 26 |
Journal | Numerical Linear Algebra with Applications |
Volume | 28 |
Issue number | 1 |
Publication status | Published - 1 Oct 2020 |
Keywords
- quadratic optimization
- multi-precision computing
- linear algebra
Fingerprint Dive into the research topics of 'Minimizing convex quadratics with variable precision Krylov methods'. Together they form a unique fingerprint.
Activities
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Minimizing convex quadratics with variable precision Krylov methods
Philippe Toint (Speaker)
28 Nov 2019Activity: Talk or presentation types › Invited talk
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ENSEEIHT-IRIT
Philippe Toint (Visiting researcher)
4 Nov 2019 → 8 Nov 2019Activity: Visiting an external institution types › Visiting an external academic institution
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Minimizing convex quadratics with variable precision Krylov methods
Philippe Toint (Speaker)
10 Oct 2019Activity: Talk or presentation types › Invited talk