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
Frank HutterELLIS Institute Tübingen & Professor, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Carlos SoaresAssociate Professor, Faculdade de Engenharia da U. Porto/External Advisor at Fraunhofer AICOSVerified email at fe.up.pt
Pieter GijsbersEindhoven University of TechnologyVerified email at tue.nl
André Carlos Ponce de Leon Ferreira...Artificial Intelligence Professor, University of São PauloVerified email at icmc.usp.br
Hendrik BlockeelDepartment of Computer Science, KU LeuvenVerified email at cs.kuleuven.be
Rafael Gomes MantovaniFederal Technology University - Paraná, campus of ApucaranaVerified email at utfpr.edu.br
Bernhard PfahringerProfessor of Computer Science, University of WaikatoVerified email at waikato.ac.nz
Geoffrey HolmesUniversity of WaikatoVerified email at waikato.ac.nz
Larisa SoldatovaProfessor, Goldsmiths, University of LondonVerified email at gold.ac.uk
Luís TorgoCanada Research Chair, Professor, Faculty of Computer Science, Dalhousie UniversityVerified email at dal.ca
Andre Luis Debiaso RossiUniversidade Estadual Paulista (UNESP)Verified email at unesp.br
Matthias FeurerLMU MunichVerified email at stat.uni-muenchen.de
Holger HoosRWTH Aachen University, Germany • Leiden University, Netherlands • University of British ColumbiaVerified email at cs.rwth-aachen.de
Giuseppe CasalicchioSenior Lecturer and Researcher, LMU Munich, Munich Center for Machine LearningVerified email at campus.lmu.de
Bo GaoHuaweiVerified email at huawei.com
Janek ThomasLudwig-Maximilians-University MunichVerified email at stat.uni-muenchen.de
Andreas Christian MuellerMicrosoftVerified email at microsoft.com

Joaquin Vanschoren

Eindhoven University of Technology

Verified email at tue.nl - Homepage

Artificial Intelligence Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Automated machine learning: methods, systems, challenges F Hutter, L Kotthoff, J Vanschoren Springer Nature, 2019	2316	2019
OpenML: networked science in machine learning J Vanschoren, JN Van Rijn, B Bischl, L Torgo ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014	1575	2014
Meta-Learning: A Survey J Vanschoren arXiv preprint arXiv:1810.03548, 2018	859	2018
Meta-learning J Vanschoren Automated machine learning: methods, systems, challenges, 35-61, 2019	414	2019
An open source AutoML benchmark P Gijsbers, E LeDell, J Thomas, S Poirier, B Bischl, J Vanschoren arXiv preprint arXiv:1907.00909, 2019	320	2019
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	308	2016
Trustllm: Trustworthiness in large language models Y Huang, L Sun, H Wang, S Wu, Q Zhang, Y Li, C Gao, Y Huang, W Lyu, ... arXiv preprint arXiv:2401.05561, 2024	250	2024
Importance of tuning hyperparameters of machine learning algorithms HJP Weerts, AC Mueller, J Vanschoren arXiv preprint arXiv:2007.07588, 2020	207	2020
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	192	2015
Openml benchmarking suites B Bischl, G Casalicchio, M Feurer, P Gijsbers, F Hutter, M Lang, ... arXiv preprint arXiv:1708.03731, 2017	160	2017
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	149	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	149	2013
Meta-features for meta-learning A Rivolli, LPF Garcia, C Soares, J Vanschoren, AC de Carvalho Knowledge-Based Systems 240, 108101, 2022	148	2022
Selecting classification algorithms with active testing R Leite, P Brazdil, J Vanschoren Machine Learning and Data Mining in Pattern Recognition: 8th International …, 2012	142	2012
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	139	2012
Dataperf: Benchmarks for data-centric ai development M Mazumder, C Banbury, X Yao, B Karlaš, W Gaviria Rojas, S Diamos, ... Advances in Neural Information Processing Systems 36, 2024	136	2024
The online performance estimation framework: heterogeneous ensemble learning for data streams JN van Rijn, G Holmes, B Pfahringer, J Vanschoren Machine Learning 107, 149-176, 2018	125	2018
OpenML: A collaborative science platform JN Van Rijn, B Bischl, L Torgo, B Gao, V Umaashankar, S Fischer, ... Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013	112	2013
Openml-python: an extensible python api for openml M Feurer, JN Van Rijn, A Kadra, P Gijsbers, N Mallik, S Ravi, A Müller, ... Journal of Machine Learning Research 22 (100), 1-5, 2021	111	2021
Fast algorithm selection using learning curves JN van Rijn, SM Abdulrahman, P Brazdil, J Vanschoren Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA …, 2015	105	2015

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