Optimal experimental design and quadratic optimization

In: Tatra Mountains Mathematical Publications, vol. 39, no. 1

Rebeca Haycroft - Luc Pronzato - Henry P. Wynn - Anatoly A. Zhigljavsky

Detaily:

Rok, strany: 2008, 115 - 123

O článku:

A well known gradient-type algorithm for solving quadratic optimization 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 $γ_k$ is chosen in accordance with a particular procedure. The asymptotic 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.

Ako citovať:

ISO 690:

Haycroft, R., Pronzato, L., Wynn, H., Zhigljavsky, A. 2008. Optimal experimental design and quadratic optimization. In Tatra Mountains Mathematical Publications, vol. 39, no.1, pp. 115-123. 1210-3195.

APA:

Haycroft, R., Pronzato, L., Wynn, H., Zhigljavsky, A. (2008). Optimal experimental design and quadratic optimization. Tatra Mountains Mathematical Publications, 39(1), 115-123. 1210-3195.