Joaquin Vanschoren - Google Scholar Citations

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	All	Since 2014
Citations	1621	1412
h-index	20	19
i10-index	36	30

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Co-authors

Jan N. van RijnColumbia UniversityVerified email at liacs.leidenuniv.nl
Bernd BischlHead of "Computational Statistics" Group, LMU MunichVerified email at stat.uni-muenchen.de
Bernhard PfahringerProfessor of Computer Science, University of WaikatoVerified email at waikato.ac.nz
Geoffrey HolmesVerified email at waikato.ac.nz
Pavel BrazdilProfessor at FEP, U.Porto, Member of LIAAD-INESC TecVerified email at inescporto.pt
Hendrik BlockeelDepartment of Computer Science, KU LeuvenVerified email at cs.kuleuven.be
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Rafael Gomes MantovaniUniversity of São PauloVerified email at icmc.usp.br
Andre Carlos Ponce de Leon Ferreira...Professor of Computer Science, Universidade de São PauloVerified email at icmc.usp.br
Luís TorgoProfessor, Faculty of Computer Science, Dalhousie UniversityVerified email at dal.ca
Larisa SoldatovaReader in Data Science, Goldsmiths, University of LondonVerified email at gold.ac.uk
Arno KnobbeLIACS, Leiden UniversityVerified email at liacs.leidenuniv.nl
Pascal KerschkeUniversity of MünsterVerified email at uni-muenster.de
Salisu Mamman Abdulrahman (PhD)Faculty Member, Kano University of Science and Technology, Wudil, KanoVerified email at fc.up.pt
André Luis Debiaso RossiAssistant Professor, State University of São Paulo (UNESP)Verified email at itapeva.unesp.br
Michel LangTU DortmundVerified email at statistik.tu-dortmund.de
Giuseppe CasalicchioLMU MünchenVerified email at campus.lmu.de
Abraham BernsteinProfessor of Computer Science, University of ZurichVerified email at ifi.uzh.ch
Holger HoosLeiden University, The Netherlands & University of British Columbia, CanadaVerified email at liacs.nl

Joaquin Vanschoren

Eindhoven University of Technology

Verified email at tue.nl - Homepage

Artificial Intelligence Machine Learning


Title	Cited by	Year
OpenML: networked science in machine learning J Vanschoren, JN Van Rijn, B Bischl, L Torgo ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014	336	2014
A survey of intelligent assistants for data analysis F Serban, J Vanschoren, JU Kietz, A Bernstein ACM Computing Surveys (CSUR) 45 (3), 31, 2013	99	2013
Experiment databases. A new way to share, organize and learn from experiments J Vanschoren, H Blockeel, B Pfahringer, G Holmes Machine learning 87 (2), 127-158, 2012	94	2012
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	92	2016
Selecting classification algorithms with active testing R Leite, P Brazdil, J Vanschoren International workshop on machine learning and data mining in pattern …, 2012	89	2012
Experiment databases: Towards an improved experimental methodology in machine learning H Blockeel, J Vanschoren European Conference on Principles of Data Mining and Knowledge Discovery, 6-17, 2007	62	2007
Automated Machine Learning-Methods, Systems, Challenges F Hutter, L Kotthoff, J Vanschoren Automated Machine Learning, 2019	50	2019
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	50	2013
Handbuch Forschungsdatenmanagement HC Hobohm, L Müller Bock+ Herchen, 2011	47	2011
Fast algorithm selection using learning curves JN van Rijn, SM Abdulrahman, P Brazdil, J Vanschoren International symposium on intelligent data analysis, 298-309, 2015	45	2015
Algorithm selection on data streams JN van Rijn, G Holmes, B Pfahringer, J Vanschoren International Conference on Discovery Science, 325-336, 2014	38	2014
Exposé: An ontology for data mining experiments J Vanschoren, L Soldatova International workshop on third generation data mining: Towards service …, 2010	37	2010
Meta-learning: A survey J Vanschoren arXiv preprint arXiv:1810.03548, 2018	36	2018
Understanding machine learning performance with experiment databases J Vanschoren lirias. kuleuven. be, no. May, 2010	36	2010
Decreasing the false alarm rate of arrhythmias in intensive care using a machine learning approach LM Eerikäinen, J Vanschoren, MJ Rooijakkers, R Vullings, RM Aarts 2015 Computing in Cardiology Conference (CinC), 293-296, 2015	27	2015
OpenML benchmarking suites and the OpenML100 B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ... arXiv preprint arXiv:1708.03731, 2017	22	2017
OpenML: An R package to connect to the machine learning platform OpenML G Casalicchio, J Bossek, M Lang, D Kirchhoff, P Kerschke, B Hofner, ... Computational Statistics, 1-15, 2017	22	2017
To tune or not to tune: recommending when to adjust SVM hyper-parameters via meta-learning RG Mantovani, ALD Rossi, J Vanschoren, B Bischl, AC Carvalho 2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015	21	2015
MDL-based analysis of time series at multiple time-scales U Vespier, A Knobbe, S Nijssen, J Vanschoren Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012	21	2012
Reduction of false arrhythmia alarms using signal selection and machine learning LM Eerikäinen, J Vanschoren, MJ Rooijakkers, R Vullings, RM Aarts Physiological measurement 37 (8), 1204, 2016	20	2016

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