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Hybridizing Target- and SHAP-Encoded Features for Algorithm Selection in Mixed-Variable Black-Box Optimization

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Τίτλος: Hybridizing Target- and SHAP-Encoded Features for Algorithm Selection in Mixed-Variable Black-Box Optimization
Συγγραφείς: Dietrich, KonstantinAff14, Aff15, Prager, Raphael PatrickAff16, Doerr, CarolaAff17, Trautmann, HeikeAff18, Aff19
Συνεισφορές: Goos, Gerhard, Series EditorAff1, Hartmanis, Juris, Founding EditorAff2, Bertino, Elisa, Editorial Board MemberAff3, Gao, Wen, Editorial Board MemberAff4, Steffen, Bernhard, Editorial Board MemberAff5, Yung, Moti, Editorial Board MemberAff6, Affenzeller, Michael, editorAff7, Winkler, Stephan M., editorAff8, Kononova, Anna V., editorAff9, Trautmann, Heike, editorAff10, Tušar, Tea, editorAff11, Machado, Penousal, editorAff12, Bäck, Thomas, editorAff13
Πηγή: Parallel Problem Solving from Nature – PPSN XVIII : 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14–18, 2024, Proceedings, Part II. 15149:154-169
Βάση Δεδομένων: Springer Nature eBooks
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