𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Automatic starting point selection for function optimization

✍ Scribed by S. P. Brooks; B. J. T. Morgan


Book ID
104639795
Publisher
Springer US
Year
1994
Tongue
English
Weight
514 KB
Volume
4
Category
Article
ISSN
0960-3174

No coin nor oath required. For personal study only.

✦ Synopsis


Traditional (non-stochastic) iterative methods for optimizing functions with multiple optima require a good procedure for selecting starting points. This paper illustrates how the selection of starting points can be made automatically by using a method based upon simulated annealing. We present a hybrid algorithm, possessing the accuracy of traditional routines, whilst incorporating the reliability of annealing methods, and illustrate its performance for a particularly complex practical problem.


πŸ“œ SIMILAR VOLUMES


Automatic model selection for the optimi
✍ N.E. Ayat; M. Cheriet; C.Y. Suen πŸ“‚ Article πŸ“… 2005 πŸ› Elsevier Science 🌐 English βš– 349 KB

This approach aims to optimize the kernel parameters and to efficiently reduce the number of support vectors, so that the generalization error can be reduced drastically. The proposed methodology suggests the use of a new model selection criterion based on the estimation of the probability of error