Joaquin Vanschoren
Cited by
Cited by
OpenML: networked science in machine learning
J Vanschoren, JN Van Rijn, B Bischl, L Torgo
ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014
Automated machine learning: methods, systems, challenges
F Hutter, L Kotthoff, J Vanschoren
Springer Nature, 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
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
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
Meta-learning: A survey
J Vanschoren
arXiv preprint arXiv:1810.03548, 2018
Selecting classification algorithms with active testing
R Leite, P Brazdil, J Vanschoren
International workshop on machine learning and data mining in pattern …, 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
Fast algorithm selection using learning curves
JN van Rijn, SM Abdulrahman, P Brazdil, J Vanschoren
International symposium on intelligent data analysis, 298-309, 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
Handbuch Forschungsdatenmanagement
HC Hobohm, L Müller
Bock+ Herchen, 2011
Algorithm selection on data streams
JN van Rijn, G Holmes, B Pfahringer, J Vanschoren
International Conference on Discovery Science, 325-336, 2014
Understanding machine learning performance with experiment databases
J Vanschoren
lirias. kuleuven. be, no, 2010
Exposé: An ontology for data mining experiments
J Vanschoren, L Soldatova
International workshop on third generation data mining: Towards service …, 2010
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
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
OpenML benchmarking suites and the OpenML100
B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ...
arXiv preprint arXiv:1708.03731, 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
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 34 (3), 977-991, 2019
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
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