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Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization

C. Benjamins, E. Raponi, A. Jankovic, C. Doerr, и M. Lindauer. GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery Special Interest Group on Genetic and Evolutionary Computation (SIGEVO), (2023)

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Joseph Doerr

Matthias Doerr

Guido Doerr

Karin Doerr

Benjamin Doerr

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Optimal Parameter Choices via Precise Black-Box Analysis.B. Doerr, C. Doerr, и J. Yang. GECCO, стр. 1123-1130. ACM, (2016)The Right Mutation Strength for Multi-Valued Decision Variables.B. Doerr, C. Doerr, и T. Kötzing. GECCO, стр. 1115-1122. ACM, (2016)Compiling a benchmarking test-suite for combinatorial black-box optimization: a position paper.O. Shir, C. Doerr, и T. Bäck. GECCO (Companion), стр. 1753-1760. ACM, (2018)The Impact of Random Initialization on the Runtime of Randomized Search Heuristics.B. Doerr, и C. Doerr. Algorithmica, 75 (3): 529-553 (2016)The unbiased black-box complexity of partition is polynomial.B. Doerr, C. Doerr, и T. Kötzing. Artif. Intell., (2014)Complexity Theory for Discrete Black-Box Optimization Heuristics.C. Doerr. CoRR, (2018)Black-Box Optimization Revisited: Improving Algorithm Selection Wizards Through Massive Benchmarking.L. Meunier, H. Rakotoarison, P. Wong, B. Rozière, J. Rapin, O. Teytaud, A. Moreau, и C. Doerr. IEEE Trans. Evol. Comput., 26 (3): 490-500 (2022)Maximizing drift is not optimal for solving OneMax.N. Buskulic, и C. Doerr. GECCO (Companion), стр. 425-426. ACM, (2019)Introducing Elitist Black-Box Models: When Does Elitist Selection Weaken the Performance of Evolutionary Algorithms?C. Doerr, и J. Lengler. CoRR, (2015)Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis.C. Benjamins, A. Jankovic, E. Raponi, K. van der Blom, M. Lindauer, и C. Doerr. CoRR, (2022)

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