Jörg Stork
Jörg Stork
PhD Student, TH Köln
Verified email at th-koeln.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
1082015
Efficient global optimization for combinatorial problems
M Zaefferer, J Stork, M Friese, A Fischbach, B Naujoks, T Bartz-Beielstein
Proceedings of the 2014 annual conference on genetic and evolutionary …, 2014
492014
Distance measures for permutations in combinatorial efficient global optimization
M Zaefferer, J Stork, T Bartz-Beielstein
International Conference on Parallel Problem Solving from Nature, 373-383, 2014
242014
rgp: R genetic programming framework
O Flasch, O Mersmann, T Bartz-Beielstein, J Stork, M Zaefferer
R package version 0.4-1, 2014
172014
SVM ensembles are better when different kernel types are combined
J Stork, R Ramos, P Koch, W Konen
Data Science, Learning by Latent Structures, and Knowledge Discovery, 191-201, 2015
112015
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
102020
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
102018
Tuning multi-objective optimization algorithms for cyclone dust separators
M Zaefferer, B Breiderhoff, B Naujoks, M Friese, J Stork, A Fischbach, ...
Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014
102014
Linear combination of distance measures for surrogate models in genetic programming
M Zaefferer, J Stork, O Flasch, T Bartz-Beielstein
International Conference on Parallel Problem Solving from Nature, 220-231, 2018
82018
A new taxonomy of continuous global optimization algorithms
J Stork, AE Eiben, T Bartz-Beielstein
arXiv preprint arXiv:1808.08818, 2018
72018
From real world data to test functions
A Fischbach, M Zaefferer, J Stork, M Friese, T Bartz-Beielstein
72016
Surrogate models for enhancing the efficiency of neuroevolution in reinforcement learning
J Stork, M Zaefferer, T Bartz-Beielstein, AE Eiben
Proceedings of the genetic and evolutionary computation conference, 934-942, 2019
62019
A new taxonomy of global optimization algorithms
J Stork, AE Eiben, T Bartz-Beielstein
Natural Computing, 1-24, 2020
52020
Improving neuroevolution efficiency by surrogate model-based optimization with phenotypic distance kernels
J Stork, M Zaefferer, T Bartz-Beielstein
International Conference on the Applications of Evolutionary Computation …, 2019
52019
Distance-based kernels for surrogate model-based neuroevolution
J Stork, M Zaefferer, T Bartz-Beielstein
arXiv preprint arXiv:1807.07839, 2018
52018
In a nutshell: Sequential parameter optimization
T Bartz-Beielstein, L Gentile, M Zaefferer
arXiv preprint arXiv:1712.04076, 2017
52017
Gecco 2017 industrial challenge: Monitoring of drinking water quality
S Chandrasekaran, M Freise, J Stork, M Rebolledo, T Bartz-Beielstein
52017
Simulation and optimization of cyclone dust separators
B Breiderhoff, T Bartz-Beielstein, B Naujoks, M Zaefferer, A Fischbach, ...
52013
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
5
Prediction of neural network performance by phenotypic modeling
A Hagg, M Zaefferer, J Stork, A Gaier
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019
42019
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Articles 1–20