Daniel Horn

Cited by

	All	Since 2017
Citations	376	353
h-index	8	8
i10-index	6	6

201520162017201820192020202120223 16 28 58 72 68 86 41

Public access

View all

5 articles

1 article

available

not available

Based on funding mandates

Co-authors

Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
Claus WeihsProfessor für Computergestützte Statistik, TU DortmundVerified email at tu-dortmund.de
Jakob BossekRWTH Aachen UniversityVerified email at aim.rwth-aachen.de
Michel LangTU Dortmund; LMU MunichVerified email at statistik.tu-dortmund.de
Jakob RichterTU DortmundVerified email at statistik.tu-dortmund.de
Tobias WagnerInstitute of Machining Technology (ISF), TU DortmundVerified email at isf.de
Tobias GlasmachersVerified email at idsia.ch
Aydin DemirciogluUniversity Hospital EssenVerified email at uk-essen.de
Janek ThomasLudwig-Maximilians-University MunichVerified email at stat.uni-muenchen.de
Dirk BiermannProfessor für Maschinenbau, TU DortmundVerified email at isf.de
Martin ZaeffererTH Köln University of Applied SciencesVerified email at th-koeln.de
Xudong SunKTH Royal Institute of TechnologyVerified email at kth.se
Kristian KerstingProfessor of AI & Machine Learning, TU Darmstadt, Co-Director of hessian.ai, Germany, CLAIRE & ELLISVerified email at cs.tu-darmstadt.de
Jens TeubnerSenior Researcher, ETH Zurich, Systems GroupVerified email at inf.ethz.ch
Malte JastrowFakultät Statistik, TU DortmundVerified email at tu-dortmund.de
Pascal KerschkeProfessor of Big Data Analytics in Transportation, TU Dresden, GermanyVerified email at tu-dresden.de
Jörg StorkSenior Data Scientist, Otto Fuchs KGVerified email at otto-fuchs.com
Carsten JentschProfessor of Business and Social Statistics, TU Dortmund UniversityVerified email at statistik.tu-dortmund.de

Daniel Horn

Statistical Methods for Big Data, TU Dortmund

Verified email at tu-dortmund.de - Homepage

Multi-Objective / Model-Based Optimization Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions B Bischl, J Richter, J Bossek, D Horn, J Thomas, M Lang arXiv preprint arXiv:1703.03373, 2017	154	2017
Model-based multi-objective optimization: taxonomy, multi-point proposal, toolbox and benchmark D Horn, T Wagner, D Biermann, C Weihs, B Bischl International Conference on Evolutionary Multi-Criterion Optimization, 64-78, 2015	75	2015
Multi-objective parameter configuration of machine learning algorithms using model-based optimization D Horn, B Bischl Computational Intelligence (SSCI), 2016 IEEE Symposium Series on, 1-8, 2016	38	2016
BBmisc: miscellaneous helper functions for B. Bischl B Bischl, M Lang, J Bossek, D Horn, J Richter, D Surmann	27*	2017
A comparative study on large scale kernelized support vector machines D Horn, A Demircioğlu, B Bischl, T Glasmachers, C Weihs Advances in Data Analysis and Classification 12 (4), 867-883, 2018	20	2018
First Investigations on Noisy Model-Based Multi-objective Optimization D Horn, M Dagge, X Sun, B Bischl International Conference on Evolutionary Multi-Criterion Optimization, 298-313, 2017	15	2017
A First Analysis of Kernels for Kriging-Based Optimization in Hierarchical Search Spaces M Zaefferer, D Horn International Conference on Parallel Problem Solving from Nature, 399-410, 2018	9	2018
Efficient global optimization: Motivation, variations and applications C Weihs, S Herbrandt, N Bauer, K Friedrichs, D Horn	9	2016
Industrial data science: developing a qualification concept for machine learning in industrial production N Bauer, L Stankiewicz, M Jastrow, D Horn, J Teubner, K Kersting, ... European Conference on Data Analysis (ECDA), 2018	8	2018
ParamHelpers: Helpers for parameters in black-box optimization, tuning, and machine learning B Bischl, M Lang, J Bossek, D Horn, K Schork, J Richter, P Kerschke R package version 1, 23, 2016	7	2016
Surrogates for hierarchical search spaces: the wedge-kernel and an automated analysis D Horn, J Stork, NJ Schüßler, M Zaefferer Proceedings of the Genetic and Evolutionary Computation Conference, 916-924, 2019	6	2019
Multi-objective selection of algorithm portfolios D Horn, B Bischl, A Demircioglu, T Glasmachers, T Wagner, C Weihs Archives of Data Science, Series A (Online First) 2 (1), 15s, 2017	2	2017
Multi-objective Selection of Algorithm Portfolios: Experimental Validation D Horn, K Schork, T Wagner International Conference on Parallel Problem Solving from Nature, 421-430, 2016	2	2016
Big Data Classification-Many Features, Many Observations C Weihs, D Horn, B Bischl	2*
Multi-objective Analysis of Machine Learning Algorithms Using Model-based Optimization Techniques D HORN	1	2019
Fast model selection by limiting SVM training times A Demircioglu, D Horn, T Glasmachers, B Bischl, C Weihs arXiv preprint arXiv:1602.03368, 2016	1	2016
Using Sequential Statistical Tests to Improve the Performance of Random Search in hyperparameter Tuning P Buczak, D Horn arXiv preprint arXiv:2112.12438, 2021		2021
Random boosting and random^ 2 forests--A random tree depth injection approach TM Krabel, TNT Tran, A Groll, D Horn, C Jentsch arXiv preprint arXiv:2009.06078, 2020		2020
B: A Comparative Study on Kernelized Support Vector Machines D Horn, A Demircioglu, B Bischl, T Glasmachers, C Weihs		2014

The system can't perform the operation now. Try again later.

Articles 1–19

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow this author

Cited by

Co-authors