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HPO $$ ELA: Investigating hyperparameter optimization landscapes by means of exploratory landscape analysis

, , , , , and . Lecture Notes in Computer Science, Springer International Publishing, Cham, (2022)

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Towards feature-free automated algorithm selection for single-objective continuous black-box optimization, , , and . 2021 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, (December 2021)Per-instance configuration of the modularized CMA-ES by means of classifier chains and exploratory landscape analysis, , , , and . 2020 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, (December 2020)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.HPO $$ ELA: Investigating hyperparameter optimization landscapes by means of exploratory landscape analysis, , , , , and . Lecture Notes in Computer Science, Springer International Publishing, Cham, (2022)A collection of deep learning-based feature-free approaches for characterizing single-objective continuous fitness landscapes, , , and . Proceedings of the Genetic and Evolutionary Computation Conference, New York, NY, USA, ACM, (July 2022)Automated algorithm selection in single-objective continuous optimization: A comparative study of deep learning and landscape analysis methods, , , and . Lecture Notes in Computer Science, Springer International Publishing, Cham, (2022)Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization, , , and . (2024)