Algorithm selection on a meta level
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2023
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oai:localhost:PNK-73452023-03-30T08:58:24Z Algorithm selection on a meta level Alexander, Tornede Lukas, Gehring Tanja, Tornede algorithmic problem Boolean satisfiability problem CC BY The problem of selecting an algorithm that appears most suitable for a specific instance of an algorithmic problem class, such as the Boolean satisfiability problem, is called instance-specific algorithm selection. Over the past decade, the problem has received considerable attention, resulting in a number of different methods for algorithm selection. Although most of these methods are based on machine learning, surprisingly little work has been done on meta learning, that is, on taking advantage of the complementarity of existing algorithm selection methods in order to combine them into a single superior algorithm selector. In this paper, we introduce the problem of meta algorithm selection, which essentially asks for the best way to combine a given set of algorithm selectors. 2023-03-30T08:58:24Z 2023-03-30T08:58:24Z 2023 Book https://link.springer.com/article/10.1007/s10994-022-06161-4 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7345 en application/pdf Springer |
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algorithmic problem Boolean satisfiability problem |
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algorithmic problem Boolean satisfiability problem Alexander, Tornede Lukas, Gehring Tanja, Tornede Algorithm selection on a meta level |
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CC BY |
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Book |
author |
Alexander, Tornede Lukas, Gehring Tanja, Tornede |
author_facet |
Alexander, Tornede Lukas, Gehring Tanja, Tornede |
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Alexander, Tornede |
title |
Algorithm selection on a meta level |
title_short |
Algorithm selection on a meta level |
title_full |
Algorithm selection on a meta level |
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Algorithm selection on a meta level |
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Algorithm selection on a meta level |
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algorithm selection on a meta level |
publisher |
Springer |
publishDate |
2023 |
url |
https://link.springer.com/article/10.1007/s10994-022-06161-4 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7345 |
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1761821915200094208 |
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