Следене
Joaquin Vanschoren
Заглавие
Позовавания
Позовавания
Година
Automated machine learning: methods, systems, challenges
F Hutter, L Kotthoff, J Vanschoren
Springer Nature, 2019
8862019
OpenML: networked science in machine learning
J Vanschoren, JN Van Rijn, B Bischl, L Torgo
ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014
8652014
Meta-learning: A survey
J Vanschoren
arXiv preprint arXiv:1810.03548, 2018
4102018
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
1962016
An open source AutoML benchmark
P Gijsbers, E LeDell, J Thomas, S Poirier, B Bischl, J Vanschoren
arXiv preprint arXiv:1907.00909, 2019
1512019
Meta-learning
J Vanschoren
Automated machine learning, 35-61, 2019
1412019
Selecting classification algorithms with active testing
R Leite, P Brazdil, J Vanschoren
International workshop on machine learning and data mining in pattern …, 2012
1272012
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
1262013
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
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
822018
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
822015
Fast algorithm selection using learning curves
JN Rijn, SM Abdulrahman, P Brazdil, J Vanschoren
International symposium on intelligent data analysis, 298-309, 2015
802015
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
772016
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
772013
Algorithm selection on data streams
JN Rijn, G Holmes, B Pfahringer, J Vanschoren
International Conference on Discovery Science, 325-336, 2014
702014
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
682007
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
632018
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
582018
Exposé: An ontology for data mining experiments
J Vanschoren, L Soldatova
International workshop on third generation data mining: Towards service …, 2010
542010
Having a blast: Meta-learning and heterogeneous ensembles for data streams
JN van Rijn, G Holmes, B Pfahringer, J Vanschoren
2015 ieee international conference on data mining, 1003-1008, 2015
522015
Системата не може да изпълни операцията сега. Опитайте отново по-късно.
Статии 1–20