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Bridging Theory and Practice Through Modular Graphical User Interfaces.

, , and . J. Multim. Process. Technol., 9 (4): 134-140 (2018)

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Benchmark-Driven Configuration of a Parallel Model-Based Optimization Algorithm., , , , and . IEEE Trans. Evol. Comput., 26 (6): 1365-1379 (2022)Hospital Capacity Planning Using Discrete Event Simulation Under Special Consideration of the COVID-19 Pandemic., , , and . CoRR, (2020)Bridging Theory and Practice Through Modular Graphical User Interfaces., , and . J. Multim. Process. Technol., 9 (4): 134-140 (2018)Optimization and Adaptation of a Resource Planning Tool for Hospitals Under Special Consideration of the COVID-19 Pandemic., , , , , , , , , and 3 other author(s). CEC, page 728-735. IEEE, (2021)Case Study II: Tuning of Gradient Boosting (xgboost)., , and . Hyperparameter Tuning for Machine and Deep Learning with R, Springer, (2023)Enhancing Surrogate-Based Optimization Through Parallelization. Studies in Computational Intelligence Springer, (2023)Feature selection for surrogate model-based optimization., , and . GECCO (Companion), page 399-400. ACM, (2019)Parallelized bayesian optimization for problems with expensive evaluation functions., , , and . GECCO Companion, page 231-232. ACM, (2020)Continuous Optimization Benchmarks by Simulation., and . PPSN (1), volume 12269 of Lecture Notes in Computer Science, page 273-286. Springer, (2020)Case Study III: Tuning of Deep Neural Networks., , and . Hyperparameter Tuning for Machine and Deep Learning with R, Springer, (2023)