Joaquin Vanschoren
Заглавие
Позовавания
Позовавания
Година
OpenML: networked science in machine learning
J Vanschoren, JN Van Rijn, B Bischl, L Torgo
ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014
7102014
Automated machine learning: methods, systems, challenges
F Hutter, L Kotthoff, J Vanschoren
Springer Nature, 2019
6012019
Meta-learning: A survey
J Vanschoren
arXiv preprint arXiv:1810.03548, 2018
2742018
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
1742016
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
1212013
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
1162012
Selecting classification algorithms with active testing
R Leite, P Brazdil, J Vanschoren
International workshop on machine learning and data mining in pattern …, 2012
1122012
An open source AutoML benchmark
P Gijsbers, E LeDell, J Thomas, S Poirier, B Bischl, J Vanschoren
arXiv preprint arXiv:1907.00909, 2019
1012019
Meta-learning
J Vanschoren
Automated Machine Learning, 35-61, 2019
872019
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
702018
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
692007
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
682013
Fast algorithm selection using learning curves
JN van Rijn, SM Abdulrahman, P Brazdil, J Vanschoren
International symposium on intelligent data analysis, 298-309, 2015
672015
Algorithm selection on data streams
JN van Rijn, G Holmes, B Pfahringer, J Vanschoren
International Conference on Discovery Science, 325-336, 2014
622014
OpenML benchmarking suites and the OpenML100
B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ...
stat 1050, 11, 2017
61*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
592015
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
552016
Exposé: An ontology for data mining experiments
J Vanschoren, L Soldatova
International workshop on third generation data mining: Towards service …, 2010
532010
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
522018
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
482018
Системата не може да изпълни операцията сега. Опитайте отново по-късно.
Статии 1–20