Petke, J;
Langdon, W;
(2019)
Genetic Improvement of Data gives Binary Logarithm from sqrt.
In:
Proceedings of the 2019 Genetic and Evolutionary Computation Conference (GECCO).
(pp. pp. 413-414).
Association for Computing Machinery (ACM): New York, NY, USA.
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Abstract
Automated search in the form of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), plus manual code changes, transforms 512 Newton-Raphson floating point start numbers from an open source GNU C library, glibc, table driven square root function to create a new bespoke custom mathematical implementation of double precision binary logarithm log2 for C in seconds.
| Type: | Proceedings paper |
|---|---|
| Title: | Genetic Improvement of Data gives Binary Logarithm from sqrt |
| Event: | 2019 Genetic and Evolutionary Computation Conference (GECCO) |
| Location: | Prague, Czech Republic |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3319619.3321954 |
| Publisher version: | http://dx.doi.org/10.1145/3319619.3321954 |
| 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 programming, GI, search based software engineering, SBSE, software maintenance of empirical constants, data transplantation |
| 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/10074376 |
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