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Optimal experimental design and quadratic optimisation

Haycroft, Rebecca, Pronzato, Luc, Wynn, Henry P. ORCID: 0000-0002-6448-1080 and Zhigljavski, Anthony (2008) Optimal experimental design and quadratic optimisation. Tatra Mountains Mathematical Publications, 29. pp. 115-123. ISSN 1210-3195

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Abstract

A well known gradient-type algorithm for solving quadratic opti- mization problems is the method of Steepest Descent. Here the Steepest Descent algorithm is generalized to a broader family of gradient algorithms, where the step-length γk is chosen in accordance with a particular procedure. The asymp- totic rate of convergence of this family is studied. To facilitate the investigation we re-write the algorithms in a normalized form which enables us to exploit a link with the theory of optimum experimental design.

Item Type: Article
Official URL: http://tatra.mat.savba.sk/
Additional Information: © 2008 The Authors
Divisions: Centre for Analysis of Time Series
Subjects: Q Science > QA Mathematics
Date Deposited: 26 Feb 2014 13:19
Last Modified: 11 Dec 2024 23:27
URI: http://eprints.lse.ac.uk/id/eprint/55874

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