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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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Self-Adjusting Weighted Expected Improvement for Bayesian Optimization., , , , and . AutoML, volume 224 of Proceedings of Machine Learning Research, page 6/1-50. PMLR, (2023)High Dimensional Bayesian Optimization Assisted by Principal Component Analysis., , , , and . PPSN (1), volume 12269 of Lecture Notes in Computer Science, page 169-183. Springer, (2020)Comparison of Bayesian Optimization Algorithms for BBOB Problems in Dimensions 10 and 60., , , and . GECCO Companion, page 2390-2393. ACM, (2023)PI is back! Switching Acquisition Functions in Bayesian Optimization, , , , , , and . 2022 NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems, arXiv, (2022)Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization., , , , and . GECCO Companion, page 483-486. ACM, (2023)Hybrid Kriging-assisted Level Set Method for Structural Topology Optimization., , , , and . IJCCI, page 70-81. ScitePress, (2019)Automated Federated Learning via Informed Pruning., , , , , , and . CoRR, (2024)High Dimensional Bayesian Optimization with Kernel Principal Component Analysis., , , and . PPSN (1), volume 13398 of Lecture Notes in Computer Science, page 118-131. Springer, (2022)Optimizing with Low Budgets: a Comparison on the Black-box Optimization Benchmarking Suite and OpenAI Gym., , , , and . CoRR, (2023)Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis, , , , , and . 6th Workshop on Meta-Learning at NeurIPS 2022, (Nov 17, 2022)