Bernd Bischl

Cited by

	All	Since 2016
Citations	3448	3036
h-index	30	29
i10-index	55	50

1100

550

275

825

2010201120122013201420152016201720182019202020219 13 24 51 108 163 258 345 538 790 1051 30

Co-authors

Michel LangTU Dortmund; LMU MunichVerified email at statistik.tu-dortmund.de
Giuseppe CasalicchioPostdoctoral Researcher, LMU Munich, Munich Center for Machine LearningVerified email at campus.lmu.de
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Olaf MersmannTH KölnVerified email at p-value.net
Heike TrautmannProfessor of Statistics, Department of Information Systems, University of Münster, GermanyVerified email at wi.uni-muenster.de
Janek ThomasFraunhofer Institute for Integrated Circuits IISVerified email at iis.fraunhofer.de
Jan N. van RijnLeiden UniversityVerified email at liacs.leidenuniv.nl
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Jakob RichterPh.D. Candidate, TU DortmundVerified email at statistik.tu-dortmund.de
Daniel HornStatistical Methods for Big Data, TU DortmundVerified email at tu-dortmund.de
Jakob BossekWestfälische Wilhelms Universität MünsterVerified email at wi.uni-muenster.de
Christoph MolnarLudwig Maximilian University of MunichVerified email at stat.uni-muenchen.de
Jörg RahnenführerTU Dortmund UniversityVerified email at statistik.tu-dortmund.de
Mike PreussUniversiteit LeidenVerified email at liacs.leidenuniv.nl
Quay AuMember of "Computational Statistics" Group, LMU MunichVerified email at stat.uni-muenchen.de
Clemens StachlPostdoctoral Researcher, Stanford UniversityVerified email at stanford.edu
Luís TorgoProfessor, Faculty of Computer Science, Dalhousie UniversityVerified email at dal.ca
Xudong SunLMU MunichVerified email at stat.uni-muenchen.de
Zachary M. JonesUniversity of WashingtonVerified email at uw.edu
Markus BühnerProfessor der LMU MünchenVerified email at lmu.de

Bernd Bischl

Chair of Statistical Learning and Data Science, LMU Munich

Verified email at stat.uni-muenchen.de - Homepage

Machine Learning Statistics


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OpenML: networked science in machine learning J Vanschoren, JN Van Rijn, B Bischl, L Torgo ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014	556	2014
mlr: Machine Learning in R B Bischl, M Lang, L Kotthoff, J Schiffner, J Richter, E Studerus, ... The Journal of Machine Learning Research 17 (1), 5938-5942, 2016	446	2016
Exploratory landscape analysis O Mersmann, B Bischl, H Trautmann, M Preuss, C Weihs, G Rudolph Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011	192	2011
Aslib: A benchmark library for algorithm selection B Bischl, P Kerschke, L Kotthoff, M Lindauer, Y Malitsky, A Fréchette, ... Artificial Intelligence 237, 41-58, 2016	146	2016
Algorithm selection based on exploratory landscape analysis and cost-sensitive learning B Bischl, O Mersmann, H Trautmann, M Preuß Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012	118	2012
Tunability: Importance of Hyperparameters of Machine Learning Algorithms. P Probst, AL Boulesteix, B Bischl J. Mach. Learn. Res. 20 (53), 1-32, 2019	113	2019
Resampling methods for meta-model validation with recommendations for evolutionary computation B Bischl, O Mersmann, H Trautmann, C Weihs Evolutionary computation 20 (2), 249-275, 2012	103	2012
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	101*	2017
iml: An R package for interpretable machine learning C Molnar, G Casalicchio, B Bischl Journal of Open Source Software 3 (26), 786, 2018	90	2018
A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem O Mersmann, B Bischl, H Trautmann, M Wagner, J Bossek, F Neumann Annals of Mathematics and Artificial Intelligence 69 (2), 151-182, 2013	69	2013
Personality traits predict smartphone usage C Stachl, S Hilbert, JQ Au, D Buschek, A De Luca, B Bischl, H Hussmann, ... European Journal of Personality 31 (6), 701-722, 2017	62	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	62	2015
BatchJobs and BatchExperiments: Abstraction mechanisms for using R in batch environments B Bischl, M Lang, O Mersmann, C Weihs Journal of Statistical Software 64 (1), 1-25, 2015	60	2015
Tuning and evolution of support vector kernels P Koch, B Bischl, O Flasch, T Bartz-Beielstein, C Weihs, W Konen Evolutionary Intelligence 5 (3), 153-170, 2012	55	2012
Benchmark for filter methods for feature selection in high-dimensional classification data A Bommert, X Sun, B Bischl, J Rahnenführer, M Lang Computational Statistics & Data Analysis 143, 106839, 2020	54	2020
OpenML: A collaborative science platform JN Van Rijn, B Bischl, L Torgo, B Gao, V Umaashankar, S Fischer, ... Joint european conference on machine learning and knowledge discovery in …, 2013	53	2013
batchtools: Tools for R to work on batch systems M Lang, B Bischl, D Surmann The Journal of Open Source Software 2 (10), 2017	50	2017
MOI-MBO: multiobjective infill for parallel model-based optimization B Bischl, S Wessing, N Bauer, K Friedrichs, C Weihs International Conference on Learning and Intelligent Optimization, 173-186, 2014	48	2014
An open source AutoML benchmark P Gijsbers, E LeDell, J Thomas, S Poirier, B Bischl, J Vanschoren arXiv preprint arXiv:1907.00909, 2019	46	2019
mlr: Machine Learning in R. R package version 2.9 B Bischl, M Lang, J Richter, J Bossek, L Judt, T Kuehn, E Studerus, ...	42*	2015

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