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Martin Zaefferer
Martin Zaefferer
DHBW Ravensburg
Verified email at dhbw-ravensburg.de - Homepage
Title
Cited by
Cited by
Year
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
2132015
Model-based methods for continuous and discrete global optimization
T Bartz-Beielstein, M Zaefferer
Applied Soft Computing 55, 154-167, 2017
1732017
Efficient Global Optimization for Combinatorial Problems
M Zaefferer, J Stork, M Friese, A Fischbach, B Naujoks, T Bartz-Beielstein
GECCO 2014 (accepted preprint), 2014
742014
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
482020
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
412020
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
332013
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
322014
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
292018
Multi-fidelity modeling and optimization of biogas plants
M Zaefferer, D Gaida, T Bartz-Beielstein
Applied Soft Computing 48, 13-28, 2016
252016
SURROGATE MODELS FOR DISCRETE OPTIMIZATION PROBLEMS
M ZAEFFERER
232018
Hyperparameter Tuning for Machine and Deep Learning with R: A Practical Guide
E Bartz, T Bartz-Beielstein, M Zaefferer, O Mersmann
Springer Nature, 2023
222023
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
22
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
212017
A gentle introduction to sequential parameter optimization
T Bartz-Beielstein, M Zaefferer
202012
Efficient Global Optimization with Indefinite Kernels
M Zaefferer, T Bartz-Beielstein
Parallel problem solving from nature - PPSN XIV, 2016
182016
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
162019
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
162018
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, ...
162016
In a Nutshell--The Sequential Parameter Optimization Toolbox
T Bartz-Beielstein, M Zaefferer, F Rehbach
arXiv preprint arXiv:1712.04076, 2017
142017
rgp: R genetic programming framework
O Flasch, O Mersmann, T Bartz-Beielstein, J Stork, M Zaefferer
R package version 0.4-1, 2014
142014
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