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PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization.

, , , , , , , , and . AutoML, volume 224 of Proceedings of Machine Learning Research, page 11/1-17. PMLR, (2023)

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Complexity Theory for Discrete Black-Box Optimization Heuristics.. CoRR, (2018)Maximizing drift is not optimal for solving OneMax., and . GECCO (Companion), page 425-426. ACM, (2019)Optimizing with Low Budgets: a Comparison on the Black-box Optimization Benchmarking Suite and OpenAI Gym., , , , and . CoRR, (2023)Lessons from the black-box: fast crossover-based genetic algorithms., , and . GECCO, page 781-788. ACM, (2013)Black-Box Optimization Revisited: Improving Algorithm Selection Wizards Through Massive Benchmarking., , , , , , , and . IEEE Trans. Evol. Comput., 26 (3): 490-500 (2022)Women@GECCO 2016 Chairs' Welcome., , , , , , , , and . GECCO (Companion), page 1447-1449. ACM, (2016)Adaptive landscape analysis., and . GECCO (Companion), page 2032-2035. ACM, (2019)Illustrating the trade-off between time, quality, and success probability in heuristic search: a discussion paper., , , and . GECCO (Companion), page 1807-1812. ACM, (2019)Benchmarking discrete optimization heuristics with IOHprofiler., , , , , and . GECCO (Companion), page 1798-1806. ACM, (2019)Fixed-target runtime analysis of the (1 + 1) EA with resampling., , , , and . GECCO (Companion), page 2068-2071. ACM, (2019)