Jan N. van Rijn - Google Scholar

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	All	Since 2015
Citations	994	964
h-index	12	12
i10-index	13	13

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201320142015201620172018201920203 21 49 75 107 217 282 232

Co-authors

Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
Luís TorgoProfessor, Faculty of Computer Science, Dalhousie UniversityVerified email at dal.ca
Bernhard PfahringerProfessor of Computer Science, University of WaikatoVerified email at waikato.ac.nz
Geoffrey HolmesUniversity of WaikatoVerified email at waikato.ac.nz
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Pavel BrazdilProfessor at FEP, U.Porto, Member of LIAAD-INESC TecVerified email at inescporto.pt
Matthias FeurerMachine Learning group, University of FreiburgVerified email at informatik.uni-freiburg.de
Michel LangTU DortmundVerified email at statistik.tu-dortmund.de
Giuseppe CasalicchioPostdoctoral Researcher, LMU Munich, Munich Center for Machine LearningVerified email at campus.lmu.de
Marius LindauerLeibniz University Hannover (Germany)Verified email at tnt.uni-hannover.de
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Andreas Christian MuellerColumbia UniversityVerified email at columbia.edu
Rafael Gomes MantovaniFederal Technology University - Paraná, campus of ApucaranaVerified email at utfpr.edu.br
Peter van der PuttenResearcher, LIACS, Leiden UniversityVerified email at liacs.leidenuniv.nl
Florian PfistererPhD Candidate, Ludwig Maximilian University of MunichVerified email at stat.uni-muenchen.de
Frank W. TakesLeiden University, University of AmsterdamVerified email at liacs.nl
Janek ThomasFraunhofer Institute for Integrated Circuits IISVerified email at iis.fraunhofer.de
Walter KostersAssociate professor, Universiteit LeidenVerified email at liacs.leidenuniv.nl
Hendrik Jan HoogeboomLIACS, Leiden UniversityVerified email at liacs.nl

Jan N. van Rijn

Leiden University

Verified email at liacs.leidenuniv.nl - Homepage

Machine Learning Artificial Intelligence


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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	514	2014
Fast algorithm selection using learning curves JN van Rijn, SM Abdulrahman, P Brazdil, J Vanschoren International symposium on intelligent data analysis, 298-309, 2015	55	2015
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
Algorithm selection on data streams JN van Rijn, G Holmes, B Pfahringer, J Vanschoren International Conference on Discovery Science, 325-336, 2014	46	2014
Hyperparameter importance across datasets JN Van Rijn, F Hutter Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	44	2018
The online performance estimation framework: heterogeneous ensemble learning for data streams JN van Rijn, G Holmes, B Pfahringer, J Vanschoren Machine Learning 107 (1), 149-176, 2018	40	2018
OpenML benchmarking suites and the OpenML100 B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ... arXiv:1708.03731, 2017	35	2017
Having a blast: Meta-learning and heterogeneous ensembles for data streams JN van Rijn, G Holmes, B Pfahringer, J Vanschoren 2015 ieee international conference on data mining, 1003-1008, 2015	24	2015
The algorithm selection competitions 2015 and 2017 M Lindauer, JN van Rijn, L Kotthoff Artificial Intelligence 272, 86-100, 2019	19*	2019
Speeding up algorithm selection using average ranking and active testing by introducing runtime SM Abdulrahman, P Brazdil, JN van Rijn, J Vanschoren Machine learning 107 (1), 79-108, 2018	18	2018
Algorithm selection via meta-learning and sample-based active testing SM Abdulrhaman, P Brazdil, JN Van Rijn, J Vanschoren	17	2015
Does feature selection improve classification? a large scale experiment in OpenML MJ Post, P Van Der Putten, JN Van Rijn International Symposium on Intelligent Data Analysis, 158-170, 2016	13	2016
Massively collaborative machine learning JN van Rijn	10	2016
Don’t rule out simple models prematurely: a large scale benchmark comparing linear and non-linear classifiers in OpenML B Strang, P van der Putten, JN van Rijn, F Hutter International Symposium on Intelligent Data Analysis, 303-315, 2018	9	2018
Open algorithm selection challenge 2017: Setup and scenarios M Lindauer, JN van Rijn, L Kotthoff Open Algorithm Selection Challenge 2017, 1-7, 2017	9	2017
Taking machine learning research online with OpenML J Vanschoren, JN van Rijn, B Bischl Proceedings of the 4th International Workshop on Big Data, Streams and …, 2015	9	2015
Playing Games: The complexity of Klondike, Mahjong, Nonograms and Animal Chess JN van Rijn	9	2012
An Empirical Study of Hyperparameter Importance Across Datasets. JN Van Rijn, F Hutter AutoML@ PKDD/ECML, 91-98, 2017	8	2017
Complexity and retrograde analysis of the game Dou Shou Qi JN Van Rijn, JK Vis	8	2013
Learning multiple defaults for machine learning algorithms F Pfisterer, JN van Rijn, P Probst, A Müller, B Bischl arXiv preprint arXiv:1811.09409, 2018	7	2018

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