Jan N. van Rijn
Jan N. van Rijn
Verified email at liacs.leidenuniv.nl - Homepage
Title
Cited by
Cited by
Year
OpenML: networked science in machine learning
J Vanschoren, JN Van Rijn, B Bischl, L Torgo
ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014
6212014
Fast algorithm selection using learning curves
JN van Rijn, SM Abdulrahman, P Brazdil, J Vanschoren
International symposium on intelligent data analysis, 298-309, 2015
642015
Hyperparameter importance across datasets
JN Van Rijn, F Hutter
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
612018
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
592013
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
532018
Algorithm selection on data streams
JN van Rijn, G Holmes, B Pfahringer, J Vanschoren
International Conference on Discovery Science, 325-336, 2014
532014
OpenML benchmarking suites and the OpenML100
B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ...
arXiv:1708.03731, 2017
45*2017
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
322015
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
242018
The algorithm selection competitions 2015 and 2017
M Lindauer, JN van Rijn, L Kotthoff
Artificial Intelligence 272, 86-100, 2019
23*2019
Does feature selection improve classification? a large scale experiment in OpenML
MJ Post, P Van Der Putten, JN Van Rijn
International Symposium on Intelligent Data Analysis, 158-170, 2016
202016
Algorithm selection via meta-learning and sample-based active testing
SM Abdulrhaman, P Brazdil, JN Van Rijn, J Vanschoren
162015
Openml-python: an extensible python api for openml
M Feurer, JN van Rijn, A Kadra, P Gijsbers, N Mallik, S Ravi, A Müller, ...
arXiv preprint arXiv:1911.02490, 2019
142019
Don’t rule out simple models prematurely: a large scale benchmark comparing linear and non-linear classifiers in OpenML
B Strang, P van der Putten, JN van Rijn, F Hutter
International Symposium on Intelligent Data Analysis, 303-315, 2018
112018
An Empirical Study of Hyperparameter Importance Across Datasets.
JN Van Rijn, F Hutter
AutoML@ PKDD/ECML, 91-98, 2017
112017
Massively collaborative machine learning
JN van Rijn
102016
Playing Games: The complexity of Klondike, Mahjong, Nonograms and Animal Chess
JN van Rijn
102012
Open algorithm selection challenge 2017: Setup and scenarios
M Lindauer, JN van Rijn, L Kotthoff
Open Algorithm Selection Challenge 2017, 1-7, 2017
92017
Taking machine learning research online with OpenML
J Vanschoren, JN van Rijn, B Bischl
Proceedings of the 4th International Workshop on Big Data, Streams and …, 2015
92015
Complexity and retrograde analysis of the game Dou Shou Qi
JN Van Rijn, JK Vis
82013
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