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Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization

, , , , and . 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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Trajectory-based Algorithm Selection with Warm-starting., , , , , and . CEC, page 1-8. IEEE, (2022)Future Trends in Digital Services and Products: Evidence from Serbian Manufacturing Firms., , , , , and . APMS (2), volume 664 of IFIP Advances in Information and Communication Technology, page 341-350. Springer, (2022)Self-Adjusting Weighted Expected Improvement for Bayesian Optimization., , , , and . AutoML, volume 224 of Proceedings of Machine Learning Research, page 6/1-50. PMLR, (2023)Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features., , , , , , and . PPSN (1), volume 13398 of Lecture Notes in Computer Science, page 46-60. Springer, (2022)Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization., , , , and . GECCO Companion, page 483-486. ACM, (2023)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)Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis, , , , , and . 6th Workshop on Meta-Learning at NeurIPS 2022, (Nov 17, 2022)Towards Feature-Based Performance Regression Using Trajectory Data., , and . EvoApplications, volume 12694 of Lecture Notes in Computer Science, page 601-617. Springer, (2021)Personalizing performance regression models to black-box optimization problems., , , , and . GECCO, page 669-677. ACM, (2021)The impact of hyper-parameter tuning for landscape-aware performance regression and algorithm selection., , , and . GECCO, page 687-696. ACM, (2021)