Krauss, O;
Langdon, WB;
(2020)
Automatically Evolving Lookup Tables for Function Approximation.
In:
Genetic Programming. EuroGP: European Conference on Genetic Programming (Part of EvoStar).
(pp. pp. 84-100).
Springer Nature
Preview |
Text
krauss_2020_EuroGP.pdf - Accepted Version Download (508kB) | Preview |
Abstract
Many functions, such as square root, are approximated and sped up with lookup tables containing pre-calculated values. We introduce an approach using genetic algorithms to evolve such lookup tables for any smooth function. It provides double precision and calculates most values to the closest bit, and outperforms reference implementations in most cases with competitive run-time performance.
| Type: | Proceedings paper |
|---|---|
| Title: | Automatically Evolving Lookup Tables for Function Approximation |
| Event: | EuroGP: 23rd European Conference on Genetic Programming (Part of EvoStar) |
| Location: | Seville, Spain |
| Dates: | 15th-17th April 2020 |
| ISBN-13: | 978-3-030-44093-0 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-44094-7_6 |
| Publisher version: | https://doi.org/10.1007/978-3-030-44094-7_6 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | Genetic Improvement, Objective function, Covariance matrix adaptation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10100133 |
Archive Staff Only
 |
View Item |
