Joaquin Vanschoren

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Jan N. van RijnLeiden UniversityVerified email at liacs.leidenuniv.nl
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
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
Bernhard PfahringerProfessor of Computer Science, University of WaikatoVerified email at waikato.ac.nz
Geoffrey HolmesUniversity of WaikatoVerified email at waikato.ac.nz
Rafael Gomes MantovaniFederal Technology University - Paraná, campus of ApucaranaVerified email at utfpr.edu.br
Hendrik BlockeelDepartment of Computer Science, KU LeuvenVerified email at cs.kuleuven.be
Andre Carlos Ponce de Leon Ferreira...Professor of Computer Science, Universidade de São PauloVerified email at icmc.usp.br
Luís TorgoCanada Research Chair, Professor, 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
Salisu Mamman Abdulrahman (PhD)Faculty Member, Kano University of Science and Technology, Wudil, KanoVerified email at fc.up.pt
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
Pascal KerschkeProfessor of Big Data Analytics in Transportation, TU Dresden, GermanyVerified email at tu-dresden.de
Matthias FeurerMachine Learning group, University of FreiburgVerified email at informatik.uni-freiburg.de
Holger HoosLeiden University, The Netherlands & University of British Columbia, CanadaVerified email at liacs.nl
Abraham BernsteinProfessor of Computer Science, University of ZurichVerified email at ifi.uzh.ch

Joaquin Vanschoren

Eindhoven University of Technology

Verified email at tue.nl - Homepage

Artificial Intelligence Machine Learning


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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	604	2014
Automated machine learning: methods, systems, challenges F Hutter, L Kotthoff, J Vanschoren Springer Nature, 2019	413	2019
Meta-learning: A survey J Vanschoren arXiv preprint arXiv:1810.03548, 2018	184	2018
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	151	2016
A survey of intelligent assistants for data analysis F Serban, J Vanschoren, JU Kietz, A Bernstein ACM Computing Surveys (CSUR) 45 (3), 1-35, 2013	119	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	111	2012
Selecting classification algorithms with active testing R Leite, P Brazdil, J Vanschoren International workshop on machine learning and data mining in pattern …, 2012	107	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	68	2007
An open source automl benchmark P Gijsbers, E LeDell, J Thomas, S Poirier, B Bischl, J Vanschoren arXiv preprint arXiv:1907.00909, 2019	65	2019
Fast algorithm selection using learning curves JN van Rijn, SM Abdulrahman, P Brazdil, J Vanschoren International symposium on intelligent data analysis, 298-309, 2015	65	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	60	2013
Handbuch Forschungsdatenmanagement HC Hobohm, L Müller Bock+ Herchen, 2011	57	2011
Meta-learning J Vanschoren Automated Machine Learning, 35-61, 2019	55	2019
Algorithm selection on data streams JN van Rijn, G Holmes, B Pfahringer, J Vanschoren International Conference on Discovery Science, 325-336, 2014	55	2014
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	54	2018
Data Augmentation using Conditional Generative Adversarial Networks for Leaf Counting in Arabidopsis Plants. Y Zhu, M Aoun, M Krijn, J Vanschoren, HT Campus BMVC, 324, 2018	48	2018
OpenML benchmarking suites and the OpenML100 B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ... stat 1050, 11, 2017	45*	2017
Effectiveness of random search in SVM hyper-parameter tuning RG Mantovani, ALD Rossi, J Vanschoren, B Bischl, AC De Carvalho 2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015	45	2015
Exposé: An ontology for data mining experiments J Vanschoren, L Soldatova International workshop on third generation data mining: Towards service …, 2010	45	2010
Hyper-parameter tuning of a decision tree induction algorithm RG Mantovani, T Horváth, R Cerri, J Vanschoren, AC de Carvalho 2016 5th Brazilian Conference on Intelligent Systems (BRACIS), 37-42, 2016	42	2016

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