- author = "Oliver Krauss and W. B. Langdon",
- title = "Automatically Evolving Lookup Tables for Function Approximation",
- booktitle = "EuroGP 2020: Proceedings of the 23rd European Conference on Genetic Programming",
- year = "2020",
- month = "15-17 " # apr,
- editor = "Ting Hu and Nuno Lourenco and Eric Medvet",
- series = "LNCS",
- volume = "12101",
- publisher = "Springer Verlag",
- address = "Seville, Spain",
- pages = "84--100",
- organisation = "EvoStar, Species",
- keywords = "genetic algorithms, genetic programming, Genetic Improvement, CMA-ES, Covariance Matrix Adaptation, Objective Function",
- isbn13 = "978-3-030-44093-0",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/krauss_2020_EuroGP.pdf",
-
URL = "
https://rdcu.be/dnYUH",
-
DOI = "
doi:10.1007/978-3-030-44094-7_6",
- size = "16 pages",
- 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.",
-
notes = "Code, paper, poster, slides, video:
https://github.com/oliver-krauss/EuroGP2020-LookupTables
http://www.evostar.org/2020/cfp_eurogp.php Part of \cite{Hu:2020:GP} EuroGP'2020 held in conjunction with EvoCOP2020, EvoMusArt2020 and EvoApplications2020",
