- author = "Fan Wu and Westley Weimer and Mark Harman and Yue Jia and Jens Krinke",
- title = "Deep Parameter Optimisation",
- booktitle = "GECCO '15: Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation",
- year = "2015",
- editor = "Sara Silva and Anna I Esparcia-Alcazar and Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and Christine Zarges and Luis Correia and Terence Soule and Mario Giacobini and Ryan Urbanowicz and Youhei Akimoto and Tobias Glasmachers and Francisco {Fernandez de Vega} and Amy Hoover and Pedro Larranaga and Marta Soto and Carlos Cotta and Francisco B. Pereira and Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and Heike Trautmann and Jean-Baptiste Mouret and Sebastian Risi and Ernesto Costa and Oliver Schuetze and Krzysztof Krawiec and Alberto Moraglio and Julian F. Miller and Pawel Widera and Stefano Cagnoni and JJ Merelo and Emma Hart and Leonardo Trujillo and Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and Carola Doerr",
- pages = "1375--1382",
- organisation = "SIGEVO",
- address = "Madrid",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- month = "11-15 " # jul,
- keywords = "genetic algorithms, genetic programming, genetic improvement, SBSE, MOGA, Parameter tuning, parameter exposure, memory allocation",
- isbn13 = "978-1-4503-3472-3",
-
URL = "
http://www.human-competitive.org/sites/default/files/wu-weimer-harman-jia-krinke-text.txt",
-
URL = "
http://www.human-competitive.org/sites/default/files/wu-weimer-harman-jia-krinke-paper.pdf",
-
DOI = "
doi:10.1145/2739480.2754648",
- size = "8 pages",
- abstract = "We introduce a mutation-based approach to automatically discover and expose deep (previously unavailable) parameters that affect a program's runtime costs. These discovered parameters, together with existing (shallow) parameters, form a search space that we tune using search-based optimisation in a bi-objective formulation that optimises both time and memory consumption. We implemented our approach and evaluated it on four real-world programs. The results show that we can improve execution time by 12percent or achieve a 21percent memory consumption reduction in the best cases. In three subjects, our deep parameter tuning results in a significant improvement over the baseline of shallow parameter tuning, demonstrating the potential value of our deep parameter extraction approach.",
-
notes = "Entered 2016 HUMIES
AST, NSGA-II, malloc, dlmalloc, Milu. 70000 lines of C code: Expresso, gawk, flex, sed.
GECCO-2015 A joint meeting of the twenty fourth international conference on genetic algorithms (ICGA-2015) and the twentieth annual genetic programming conference (GP-2015)",
