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Joaquin Vanschoren
Joaquin Vanschoren
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Titel
Zitiert von
Zitiert von
Jahr
Automated machine learning: methods, systems, challenges
F Hutter, L Kotthoff, J Vanschoren
Springer Nature, 2019
10762019
OpenML: networked science in machine learning
J Vanschoren, JN Van Rijn, B Bischl, L Torgo
ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014
9792014
Meta-learning: A survey
J Vanschoren
arXiv preprint arXiv:1810.03548, 2018
4972018
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
2072016
Meta-learning
J Vanschoren
Automated machine learning, 35-61, 2019
1822019
An open source AutoML benchmark
P Gijsbers, E LeDell, J Thomas, S Poirier, B Bischl, J Vanschoren
arXiv preprint arXiv:1907.00909, 2019
1812019
Selecting classification algorithms with active testing
R Leite, P Brazdil, J Vanschoren
International workshop on machine learning and data mining in pattern …, 2012
1312012
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
1292013
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
1232012
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
972015
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
922018
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
922016
Fast algorithm selection using learning curves
JN Rijn, SM Abdulrahman, P Brazdil, J Vanschoren
International symposium on intelligent data analysis, 298-309, 2015
852015
OpenML: A collaborative science platform
JN Rijn, B Bischl, L Torgo, B Gao, V Umaashankar, S Fischer, P Winter, ...
Joint european conference on machine learning and knowledge discovery in …, 2013
792013
Algorithm selection on data streams
JN Rijn, G Holmes, B Pfahringer, J Vanschoren
International Conference on Discovery Science, 325-336, 2014
732014
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
722007
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
682018
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery
I Olier, N Sadawi, GR Bickerton, J Vanschoren, C Grosan, L Soldatova, ...
Machine Learning 107 (1), 285-311, 2018
652018
Importance of tuning hyperparameters of machine learning algorithms
HJP Weerts, AC Mueller, J Vanschoren
arXiv preprint arXiv:2007.07588, 2020
582020
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
572018
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