Jan N. van Rijn
Jan N. van Rijn
Columbia University
Verified email at liacs.leidenuniv.nl - Homepage
TitleCited byYear
OpenML: networked science in machine learning
J Vanschoren, JN Van Rijn, B Bischl, L Torgo
ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014
2742014
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
462013
Fast algorithm selection using learning curves
JN van Rijn, SM Abdulrahman, P Brazdil, J Vanschoren
International symposium on intelligent data analysis, 298-309, 2015
402015
Algorithm selection on data streams
JN van Rijn, G Holmes, B Pfahringer, J Vanschoren
International Conference on Discovery Science, 325-336, 2014
352014
The elevation of sarcoplasmic reticulum Ca2+-ATPase levels by thyroid hormone in the L6 muscle cell line is potentiated by insulin-like growth factor-I
A Muller, C Van Hardeveld, WS Simonides, J Van Rijn
Biochemical journal 275 (1), 35-40, 1991
181991
Hyperparameter importance across datasets
JN van Rijn, F Hutter
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
172018
Ca2+ homeostasis and fast-type sarcoplasmic reticulum Ca2+-ATPase expression in L6 muscle cells. Role of thyroid hormone
A Muller, C Van Hardeveld, WS Simonides, J Van Rijn
Biochemical Journal 283 (3), 713-718, 1992
171992
OpenML benchmarking suites and the OpenML100
B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ...
arXiv preprint arXiv:1708.03731, 2017
152017
Algorithm selection via meta-learning and sample-based active testing
SM Abdulrhaman, P Brazdil, JN Van Rijn, J Vanschoren
152015
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
132015
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
122016
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
112018
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
112018
Playing Games: The complexity of Klondike, Mahjong, Nonograms and Animal Chess
JN van Rijn
82012
Massively collaborative machine learning
JN van Rijn
IPA Dissertation Series, 2016
72016
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
72015
A RapidMiner extension for Open Machine Learning
JN Van Rijn, V Umaashankar, S Fischer, B Bischl, L Torgo, B Gao, ...
RCOMM 2013, 2013
72013
Open algorithm selection challenge 2017: Setup and scenarios
M Lindauer, JN van Rijn, L Kotthoff
Open Algorithm Selection Challenge 2017, 1-7, 2017
62017
Complexity and retrograde analysis of the game Dou Shou Qi
JN Van Rijn, JK Vis
62013
Openml: Networked science in machine learning. SIGKDD Explorations 15 (2), 49–60 (2013)
J Vanschoren, JN van Rijn, B Bischl, L Torgo
6
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