Library Header Image
LSE Research Online LSE Library Services

Optimal experimental design and quadratic optimisation

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

Full text not available from this repository.


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:
Additional Information: © 2008 The Authors
Divisions: Centre for Analysis of Time Series
Subjects: Q Science > QA Mathematics
Sets: Research centres and groups > Centre for the Analysis of Time Series (CATS)
Research centres and groups > Decision Support and Risk Group (DSRG)
Date Deposited: 26 Feb 2014 13:19
Last Modified: 21 Aug 2021 23:11

Actions (login required)

View Item View Item