Bernd Bischl

Cited by

	All	Since 2016
Citations	3551	3115
h-index	31	29
i10-index	52	48

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550

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825

2011201220132014201520162017201820192020202113 26 58 111 167 251 349 550 797 1072 71

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
Janek ThomasFraunhofer Institute for Integrated Circuits IISVerified email at iis.fraunhofer.de
Heike TrautmannProfessor of Statistics, Department of Information Systems, University of Münster, GermanyVerified email at wi.uni-muenster.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
Florian PfistererPhD Candidate, Ludwig Maximilian University of MunichVerified email at stat.uni-muenchen.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	557	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	459	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	122	2012
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	119	2012
Tunability: Importance of hyperparameters of machine learning algorithms. P Probst, AL Boulesteix, B Bischl J. Mach. Learn. Res. 20 (53), 1-32, 2019	118	2019
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	107*	2017
iml: An R package for interpretable machine learning C Molnar, G Casalicchio, B Bischl Journal of Open Source Software 3 (26), 786, 2018	92	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	71	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	64	2017
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	62	2020
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	62	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	60	2012
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	55	2013
An open source automl benchmark P Gijsbers, E LeDell, J Thomas, S Poirier, B Bischl, J Vanschoren arXiv preprint arXiv:1907.00909, 2019	52	2019
batchtools: Tools for R to work on batch systems M Lang, B Bischl, D Surmann The Journal of Open Source Software 2 (10), 2017	52	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	50	2014
Support vector machines on large data sets: Simple parallel approaches O Meyer, B Bischl, C Weihs Data Analysis, Machine Learning and Knowledge Discovery, 87-95, 2014	48	2014

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