Comparison of parallel surrogate-assisted optimization approaches. - Frederik Rehbach; Martin Zaefferer; Jörg Stork; Thomas Bartz-Beielstein (GECCO, 2018)

Bridging Theory and Practice Through Modular Graphical User Interfaces. - Frederik Rehbach; Jörg Stork; Thomas Bartz-Beielstein (J. Multim. Process. Technol., 2018)

Feature selection for surrogate model-based optimization. - Frederik Rehbach; Lorenzo Gentile; Thomas Bartz-Beielstein (GECCO (Companion), 2019)

Parallelized bayesian optimization for problems with expensive evaluation functions. - Margarita Alejandra Rebolledo Coy; Frederik Rehbach; A. E. Eiben; Thomas Bartz-Beielstein (GECCO Companion, 2020)

Variable reduction for surrogate-based optimization. - Frederik Rehbach; Lorenzo Gentile; Thomas Bartz-Beielstein (GECCO, 2020)

Expected improvement versus predicted value in surrogate-based optimization. - Frederik Rehbach; Martin Zaefferer; Boris Naujoks; Thomas Bartz-Beielstein (GECCO, 2020)

Parallelized Bayesian Optimization for Expensive Robot Controller Evolution. - Margarita Alejandra Rebolledo Coy; Frederik Rehbach; A. E. Eiben; Thomas Bartz-Beielstein (PPSN (1), 2020)

Continuous Optimization Benchmarks by Simulation. - Martin Zaefferer; Frederik Rehbach (PPSN (1), 2020)

Optimization of High-dimensional Simulation Models Using Synthetic Data. - Thomas Bartz-Beielstein; Eva Bartz; Frederik Rehbach; Olaf Mersmann (CoRR, 2020)

Hospital Capacity Planning Using Discrete Event Simulation Under Special Consideration of the COVID-19 Pandemic. - Thomas Bartz-Beielstein; Frederik Rehbach; Olaf Mersmann; Eva Bartz (CoRR, 2020)

Optimization and Adaptation of a Resource Planning Tool for Hospitals Under Special Consideration of the COVID-19 Pandemic. - Thomas Bartz-Beielstein; Marcel Dröscher; Alpar Gür; Alexander Hinterleitner; Tom Lawton; Olaf Mersmann; Dessislava Peeva; Lennard Reese; Nicolas Rehbach; Frederik Rehbach; Amrita Sen; Aleksandr Subbotin; et al. (CEC, 2021)

Resource planning for hospitals under special consideration of the COVID-19 pandemic: optimization and sensitivity analysis. - Thomas Bartz-Beielstein; Marcel Dröscher; Alpar Gür; Alexander Hinterleitner; Olaf Mersmann; Dessislava Peeva; Lennard Reese; Nicolas Rehbach; Frederik Rehbach; A. Sen; Aleksandr Subbotin; Martin Zaefferer (GECCO Companion, 2021)

Resource Planning for Hospitals Under Special Consideration of the COVID-19 Pandemic: Optimization and Sensitivity Analysis. - Thomas Bartz-Beielstein; Marcel Dröscher; Alpar Gür; Alexander Hinterleitner; Olaf Mersmann; Dessislava Peeva; Lennard Reese; Nicolas Rehbach; Frederik Rehbach; Amrita Sen; Aleksandr Subbotin; Martin Zaefferer (CoRR, 2021)

Benchmark-Driven Configuration of a Parallel Model-Based Optimization Algorithm. - Frederik Rehbach; Martin Zaefferer; Andreas Fischbach; Günter Rudolph; Thomas Bartz-Beielstein (IEEE Trans. Evol. Comput., 2022)

Case Study II: Tuning of Gradient Boosting (xgboost). - Thomas Bartz-Beielstein; Sowmya Chandrasekaran; Frederik Rehbach (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Case Study III: Tuning of Deep Neural Networks. - Thomas Bartz-Beielstein; Sowmya Chandrasekaran; Frederik Rehbach (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Case Study I: Tuning Random Forest (Ranger). - Thomas Bartz-Beielstein; Sowmya Chandrasekaran; Frederik Rehbach; Martin Zaefferer (Hyperparameter Tuning for Machine and Deep Learning with R, 2023)

Enhancing Surrogate-Based Optimization Through Parallelization - Frederik Rehbach (Springer, 2023)