Bernd Bischl - Google Scholar

Cited by

	All	Since 2015
Citations	3066	2824
h-index	29	28
i10-index	48	45

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201020112012201320142015201620172018201920209 13 24 51 109 160 255 345 531 799 709

Co-authors

Michel LangTU DortmundVerified 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
Mike PreussUniversiteit LeidenVerified email at liacs.leidenuniv.nl
Jörg RahnenführerTU Dortmund UniversityVerified email at statistik.tu-dortmund.de
Christoph MolnarLudwig Maximilian University of MunichVerified email at stat.uni-muenchen.de
Quay AuMember of "Computational Statistics" Group, LMU MunichVerified email at stat.uni-muenchen.de
Luís TorgoProfessor, Faculty of Computer Science, Dalhousie UniversityVerified email at dal.ca
Clemens StachlPostdoctoral Researcher, Stanford UniversityVerified email at stanford.edu
Zachary M. JonesUniversity of WashingtonVerified email at uw.edu
Xudong SunLMU MunichVerified email at stat.uni-muenchen.de
Pascal KerschkeUniversity of MünsterVerified email at uni-muenster.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	493	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	405	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	181	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	132	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	113	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	95	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	90*	2017
Tunability: Importance of Hyperparameters of Machine Learning Algorithms. P Probst, AL Boulesteix, B Bischl J. Mach. Learn. Res. 20 (53), 1-32, 2019	79	2019
iml: An R package for interpretable machine learning C Molnar, G Casalicchio, B Bischl Journal of Open Source Software 3 (26), 786, 2018	67	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	65	2013
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	59	2015
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	57	2015
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	55	2017
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
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	53	2012
batchtools: Tools for R to work on batch systems M Lang, B Bischl, D Surmann The Journal of Open Source Software 2 (10), 2017	46	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	45	2014
mlr: Machine Learning in R. R package version 2.9 B Bischl, M Lang, J Richter, J Bossek, L Judt, T Kuehn, E Studerus, ...	38*	2015
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	38	2014
Analyzing the BBOB results by means of benchmarking concepts O Mersmann, M Preuss, H Trautmann, B Bischl, C Weihs Evolutionary Computation 23 (1), 161-185, 2015	37	2015

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