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Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features

, , , , , , , and . FOGA 2023, page 129--139. United States, Association for Computing Machinery, (Aug 30, 2023)Publisher Copyright: © 2023 ACM.; 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2023, FOGA 2023 ; Conference date: 30-08-2023 Through 01-09-2023.
DOI: 10.1145/3594805.3607136

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Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features, , , , , , , and . FOGA 2023, page 129--139. United States, Association for Computing Machinery, (Aug 30, 2023)Publisher Copyright: © 2023 ACM.; 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2023, FOGA 2023 ; Conference date: 30-08-2023 Through 01-09-2023.Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization, , , and . (2024)Evaluation of Algorithms from the Nevergrad Toolbox on the Strictly Box-Constrained SBOX-COST Benchmarking Suite, and . Proceedings of the Companion Conference on Genetic and Evolutionary Computation, page 2326–2329. New York, NY, USA, Association for Computing Machinery, (2023)Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization, , , and . (2024)