Matches in SemOpenAlex for { <https://semopenalex.org/work/W3138971189> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W3138971189 endingPage "2749" @default.
- W3138971189 startingPage "2749" @default.
- W3138971189 abstract "Many of the works conducted on algorithm selection strategies—methods that choose a suitable solving method for a particular problem—start from scratch since only a few investigations on reusable components of such methods are found in the literature. Additionally, researchers might unintentionally omit some implementation details when documenting the algorithm selection strategy. This makes it difficult for others to reproduce the behavior obtained by such an approach. To address these problems, we propose to rely on existing techniques from the Machine Learning realm to speed-up the generation of algorithm selection strategies while improving the modularity and reproducibility of the research. The proposed solution model is implemented on a domain-independent Machine Learning module that executes the core mechanism of the algorithm selection task. The algorithm selection strategies produced in this work are implemented and tested rapidly compared against the time it would take to build a similar approach from scratch. We produce four novel algorithm selectors based on Machine Learning for constraint satisfaction problems to verify our approach. Our data suggest that these algorithms outperform the best performing algorithm on a set of test instances. For example, the algorithm selectors Multiclass Neural Network (MNN) and Multiclass Logistic Regression (MLR), powered by a neural network and linear regression, respectively, reduced the search cost (in terms of consistency checks) of the best performing heuristic (KAPPA), on average, by 49% for the instances considered for this work." @default.
- W3138971189 created "2021-03-29" @default.
- W3138971189 creator A5027131130 @default.
- W3138971189 creator A5028807044 @default.
- W3138971189 creator A5040026225 @default.
- W3138971189 creator A5041843953 @default.
- W3138971189 creator A5049386377 @default.
- W3138971189 creator A5086193689 @default.
- W3138971189 date "2021-03-18" @default.
- W3138971189 modified "2023-10-18" @default.
- W3138971189 title "A General Framework Based on Machine Learning for Algorithm Selection in Constraint Satisfaction Problems" @default.
- W3138971189 cites W1134221749 @default.
- W3138971189 cites W1258972194 @default.
- W3138971189 cites W1471542436 @default.
- W3138971189 cites W1487986911 @default.
- W3138971189 cites W1495775210 @default.
- W3138971189 cites W1526726828 @default.
- W3138971189 cites W1539214632 @default.
- W3138971189 cites W1541288193 @default.
- W3138971189 cites W1967715425 @default.
- W3138971189 cites W1996264924 @default.
- W3138971189 cites W1997807546 @default.
- W3138971189 cites W2023785065 @default.
- W3138971189 cites W2024060531 @default.
- W3138971189 cites W2044742178 @default.
- W3138971189 cites W2072441740 @default.
- W3138971189 cites W2089213632 @default.
- W3138971189 cites W2095435811 @default.
- W3138971189 cites W2096357471 @default.
- W3138971189 cites W2119924737 @default.
- W3138971189 cites W2121766240 @default.
- W3138971189 cites W2133510907 @default.
- W3138971189 cites W2147148915 @default.
- W3138971189 cites W2151554678 @default.
- W3138971189 cites W2221935446 @default.
- W3138971189 cites W2257516073 @default.
- W3138971189 cites W2346152773 @default.
- W3138971189 cites W2727052904 @default.
- W3138971189 cites W2795799780 @default.
- W3138971189 cites W2894900521 @default.
- W3138971189 cites W2895357514 @default.
- W3138971189 cites W2898032212 @default.
- W3138971189 cites W2911169884 @default.
- W3138971189 cites W2966907151 @default.
- W3138971189 cites W2967783393 @default.
- W3138971189 cites W2968840829 @default.
- W3138971189 cites W3098687075 @default.
- W3138971189 cites W54298403 @default.
- W3138971189 doi "https://doi.org/10.3390/app11062749" @default.
- W3138971189 hasPublicationYear "2021" @default.
- W3138971189 type Work @default.
- W3138971189 sameAs 3138971189 @default.
- W3138971189 citedByCount "2" @default.
- W3138971189 countsByYear W31389711892022 @default.
- W3138971189 countsByYear W31389711892023 @default.
- W3138971189 crossrefType "journal-article" @default.
- W3138971189 hasAuthorship W3138971189A5027131130 @default.
- W3138971189 hasAuthorship W3138971189A5028807044 @default.
- W3138971189 hasAuthorship W3138971189A5040026225 @default.
- W3138971189 hasAuthorship W3138971189A5041843953 @default.
- W3138971189 hasAuthorship W3138971189A5049386377 @default.
- W3138971189 hasAuthorship W3138971189A5086193689 @default.
- W3138971189 hasBestOaLocation W31389711891 @default.
- W3138971189 hasConcept C11413529 @default.
- W3138971189 hasConcept C119857082 @default.
- W3138971189 hasConcept C154945302 @default.
- W3138971189 hasConcept C177264268 @default.
- W3138971189 hasConcept C199360897 @default.
- W3138971189 hasConcept C41008148 @default.
- W3138971189 hasConcept C50644808 @default.
- W3138971189 hasConcept C81917197 @default.
- W3138971189 hasConceptScore W3138971189C11413529 @default.
- W3138971189 hasConceptScore W3138971189C119857082 @default.
- W3138971189 hasConceptScore W3138971189C154945302 @default.
- W3138971189 hasConceptScore W3138971189C177264268 @default.
- W3138971189 hasConceptScore W3138971189C199360897 @default.
- W3138971189 hasConceptScore W3138971189C41008148 @default.
- W3138971189 hasConceptScore W3138971189C50644808 @default.
- W3138971189 hasConceptScore W3138971189C81917197 @default.
- W3138971189 hasIssue "6" @default.
- W3138971189 hasLocation W31389711891 @default.
- W3138971189 hasOpenAccess W3138971189 @default.
- W3138971189 hasPrimaryLocation W31389711891 @default.
- W3138971189 hasRelatedWork W2386387936 @default.
- W3138971189 hasRelatedWork W2961085424 @default.
- W3138971189 hasRelatedWork W3046775127 @default.
- W3138971189 hasRelatedWork W3170094116 @default.
- W3138971189 hasRelatedWork W4205958290 @default.
- W3138971189 hasRelatedWork W4285260836 @default.
- W3138971189 hasRelatedWork W4286629047 @default.
- W3138971189 hasRelatedWork W4306321456 @default.
- W3138971189 hasRelatedWork W4306674287 @default.
- W3138971189 hasRelatedWork W4224009465 @default.
- W3138971189 hasVolume "11" @default.
- W3138971189 isParatext "false" @default.
- W3138971189 isRetracted "false" @default.
- W3138971189 magId "3138971189" @default.
- W3138971189 workType "article" @default.