Swan, Jeremiah and Burles, Nathan John orcid.org/0000-0003-3030-1675 (2015) Hyper-quicksort: energy efficient sorting via the Templar framework for Template Method Hyper-heuristics. In: 39th CREST Open Workshop: Measuring, Testing and Optimising Computational Energy Consumption, 23-24 Feb 2015, UCL.
Abstract
Scalability remains an issue for program synthesis: - We don’t yet know how to generate sizeable algorithms from scratch. - Generative approaches such as GP still work best at the scale of expressions (though some recent promising results). - Formal approaches require a strong mathematical background. - ... but human ingenuity already provides a vast repertoire of specialized algorithms, usually with known asymptotic behaviour. Given these limitations, how can we best use generative hyper-heuristics to improve upon human-designed algorithms?
Metadata
Authors/Creators: |
|
---|---|
Dates: |
|
Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 21 Jul 2015 16:00 |
Last Modified: | 06 Dec 2023 10:32 |
Status: | Published |
Refereed: | No |
Download
Description: hyper-quicksort-energy-efficient-sorting-via-the-templar-framework-for-template-method-hyper-heuristics