Martin Zaefferer

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Thomas Bartz-BeielsteinTH Koeln, Institute for Data Science, Engineering, and AnalyticsVerified email at th-koeln.de
Jörg StorkSenior Data Scientist, Otto Fuchs KGVerified email at otto-fuchs.com
Boris NaujoksCologne University of Applied SciencesVerified email at fh-koeln.de
Martina Echtenbruck (née Friese)Cologne University of Applied SciencesVerified email at th-koeln.de
Frederik RehbachCologne University of Applied SciencesVerified email at th-koeln.de
Steffen MoritzResearch Associate, Technische Hochschule KölnVerified email at th-koeln.de
Wolfgang KonenProfessor for Computer Science & Mathematics, Cologne University of Applied SciencesVerified email at th-koeln.de
A.E. EibenProfessor of Computational Intelligence, Vrije Universiteit AmsterdamVerified email at vu.nl
Tea TušarSenior Research Associate, Jožef Stefan InstituteVerified email at ijs.si
Tobias WagnerInstitute of Machining Technology (ISF), TU DortmundVerified email at isf.de
Michael T.M. Emmerich (Dr. rer. nat.)Professor in Multiobjective OptimizationVerified email at liacs.nl
Daniel HornStatistical Methods for Big Data, TU DortmundVerified email at tu-dortmund.de
Lorenzo GentileMarie Curie Early Stage Researcher & PhD candidate, TH Köln, University of StrathclydeVerified email at th-koeln.de
Daniel GaidaTH KölnVerified email at th-koeln.de
Tinkle ChughLecturer (Assistant Professor) in Computer Science, University of ExeterVerified email at exeter.ac.uk
Alma RahatAssociate Professor of Data Science, Swansea UniversityVerified email at swansea.ac.uk
Vanessa VolzCentrum Wiskunde & Informatica (CWI)Verified email at cwi.nl
Mike PreussUniversiteit LeidenVerified email at liacs.leidenuniv.nl
Dr. Patrick KochData Scientist

Martin Zaefferer

DHBW Ravensburg

Verified email at dhbw-ravensburg.de - Homepage

Optimization Surrogate Model Based Optimization Machine Learning Statistics


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Comparison of different Methods for Univariate Time Series Imputation in R S Moritz, A Sardá, T Bartz-Beielstein, M Zaefferer, J Stork arXiv preprint arXiv:1510.03924, 2015	223	2015
Model-based methods for continuous and discrete global optimization T Bartz-Beielstein, M Zaefferer Applied Soft Computing 55, 154-167, 2017	183	2017
Efficient Global Optimization for Combinatorial Problems M Zaefferer, J Stork, M Friese, A Fischbach, B Naujoks, T Bartz-Beielstein GECCO 2014 (accepted preprint), 2014	79	2014
Open Issues in Surrogate-Assisted Optimization J Stork, M Friese, M Zaefferer, T Bartz-Beielstein, A Fischbach, ... High-Performance Simulation-Based Optimization, 225-244, 2020	55	2020
Expected improvement versus predicted value in surrogate-based optimization F Rehbach, M Zaefferer, B Naujoks, T Bartz-Beielstein Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 868-876, 2020	43	2020
Hyperparameter Tuning for Machine and Deep Learning with R: A Practical Guide E Bartz, T Bartz-Beielstein, M Zaefferer, O Mersmann Springer Nature, 2023	42	2023
Distance measures for permutations in combinatorial efficient global optimization M Zaefferer, J Stork, T Bartz-Beielstein Parallel Problem Solving from Nature–PPSN XIII: 13th International …, 2014	38	2014
A Case Study on Multi-Criteria Optimization of an Event Detection Software under Limited Budgets M Zaefferer, T Bartz-Beielstein, B Naujoks, T Wagner, M Emmerich	33	2013
Comparison of parallel surrogate-assisted optimization approaches F Rehbach, M Zaefferer, J Stork, T Bartz-Beielstein Proceedings of the Genetic and Evolutionary Computation Conference, 1348-1355, 2018	31	2018
Multi-fidelity modeling and optimization of biogas plants M Zaefferer, D Gaida, T Bartz-Beielstein Applied Soft Computing 48, 13-28, 2016	25	2016
Comparison of different methods for univariate time series imputation in R. arXiv 2015 S Moritz, A Sardá, T Bartz-Beielstein, M Zaefferer, J Stork arXiv preprint arXiv:1510.03924, 0	24
SURROGATE MODELS FOR DISCRETE OPTIMIZATION PROBLEMS M ZAEFFERER	23	2018
Metamodel-based optimization of hot rolling processes in the metal industry C Jung, M Zaefferer, T Bartz-Beielstein, G Rudolph The International Journal of Advanced Manufacturing Technology 90, 421-435, 2017	21	2017
A gentle introduction to sequential parameter optimization T Bartz-Beielstein, M Zaefferer	20	2012
Efficient Global Optimization with Indefinite Kernels M Zaefferer, T Bartz-Beielstein Parallel problem solving from nature - PPSN XIV, 2016	18	2016
Improving neuroevolution efficiency by surrogate model-based optimization with phenotypic distance kernels J Stork, M Zaefferer, T Bartz-Beielstein Applications of Evolutionary Computation: 22nd International Conference …, 2019	17	2019
A first analysis of kernels for kriging-based optimization in hierarchical search spaces M Zaefferer, D Horn Parallel Problem Solving from Nature–PPSN XV: 15th International Conference …, 2018	16	2018
Data Preprocessing: A New Algorithm for Univariate Imputation Designed Specifically for Industrial Needs S Chandrasekaran, M Zaefferer, S Moritz, J Stork, M Friese, A Fischbach, ...	16	2016
In a Nutshell--The Sequential Parameter Optimization Toolbox T Bartz-Beielstein, M Zaefferer, F Rehbach arXiv preprint arXiv:1712.04076, 2017	15	2017
rgp: R genetic programming framework O Flasch, O Mersmann, T Bartz-Beielstein, J Stork, M Zaefferer R package version 0.4-1, 2014	14	2014

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