𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Consistency of a myopic Bayesian algorithm for one-dimensional global optimization

✍ Scribed by James M. Calvin

Publisher
Springer US
Year
1993
Tongue
English
Weight
413 KB
Volume
3
Category
Article
ISSN
0925-5001

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

One-Dimensional global optimization for
One-Dimensional global optimization for observations with noise
✍ J.M. Calvin; A. ΕΏilinskas πŸ“‚ Article πŸ“… 2005 πŸ› Elsevier Science 🌐 English βš– 643 KB

A problem of one-dlmenstonal global optlmmatlon m the presence of noise is considered The approach is based on modeling the objective function as a standard Wiener process which is observed with independent Gausslan noise. An asymptotic bound for the average error ]s estimated for the nonadaptive st

The application of a unified Bayesian st
The application of a unified Bayesian stopping criterion in competing parallel algorithms for global optimization
✍ H.P.J. Bolton; A.A. Groenwold; J.A. Snyman πŸ“‚ Article πŸ“… 2004 πŸ› Elsevier Science 🌐 English βš– 880 KB

The unconstrained global programming problem is addressed using a multistart, multialgorithm infrastructure, in which different algorithms compete in parallel for a contribution towards a single global stopping criterion, denoted the unified Bayesian global stopping criterion. The use of different

On Timonov's algorithm for global optimi
On Timonov's algorithm for global optimization of univariate Lipschitz functions
✍ Pierre Hansen; Brigitte Jaumard; Shi-Hui Lu πŸ“‚ Article πŸ“… 1991 πŸ› Springer US 🌐 English βš– 477 KB

Timonov proposes an algorithm for global maximization of univariate Lipschitz functions in which successive evaluation points arc chosen in order to ensure at each iteration a maximal expected reduction of the "region of indeterminacy", which contains all globally optimal points. It is shown that su