Alumni

Jan van Rijn

Postal address
Institut für Informatik
Albert-Ludwigs-Universität Freiburg
Sekretariat Hutter/Maschinelles Lernen
Georges-Köhler-Allee 074
79110 Freiburg, Germany
Fax
+49 761 203-74217
Office
Building 74, Room 00-017
Marker

Projects

  • OpenML Open Machine Learning

Publications

2021

Feurer, Matthias; van Rijn, Jan N; Kadra, Arlind; Gijsbers, Pieter; Mallik, Neeratyoy; Ravi, Sahithya; Müller, Andreas; Vanschoren, Joaquin; Hutter, Frank

OpenML-Python: an extensible Python API for OpenML Journal Article

In: Journal of Machine Learning Research, 22 (100), pp. 1-5, 2021.

2019

Bischl, Bernd; Casalicchio, Giuseppe; Feurer, Matthias; Hutter, Frank; Lang, Michel; Mantovani, Rafael G; van Rijn, Jan N; Vanschoren, Joaquin

OpenML Benchmarking Suites Journal Article

In: arXiv, 1708.0373v2 , pp. 1-6, 2019.

2018

Lindauer, M; van Rijn, J N; Kotthoff, L

The Algorithm Selection Competitions 2015 and 2017 Journal Article

In: Artificial Intelligence, pp. 1-35, 2018.

Abdulrahman, S M; Brazdil, P; van Rijn, J N; Vanschoren, J

Speeding up algorithm selection using average ranking and active testing by introducing runtime Inproceedings

In: Machine Learning, pp. 79–108, 2018.

van Rijn, J N; Holmes, G; Pfahringer, B; Vanschoren, J

The online performance estimation framework: heterogeneous ensemble learning for data streams Inproceedings

In: Machine Learning, pp. 149–176, 2018.

van Rijn, J N; Hutter, F

Hyperparameter Importance Across Datasets Journal Article

In: SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), 2018.

2017

Lindauer, Marius; van Rijn, Jan N; Kotthoff, Lars

Open Algorithm Selection Challenge 2017: Setup and Scenarios Inproceedings

In: Lindauer, Marius; van Rijn, Jan N; Kotthoff, Lars (Ed.): Proceedings of the Open Algorithm Selection Challenge, pp. 1–7, PMLR, Brussels, Belgium, 2017.

Bischl, Bernd; Casalicchio, Giuseppe; Feurer, Matthias; Hutter, Frank; Lang, Michel; Mantovani, Rafael G; van Rijn, Jan N; Vanschoren, Joaquin

OpenML Benchmarking Suites and the OpenML100 Journal Article

In: arXiv, 1708.0373v1 , pp. 1-6, 2017.

van Rijn, J N; Hutter, F

An Empirical Study of Hyperparameter Importance Across Datasets Inproceedings

In: Proceedings of the International Workshop on Automatic Selection, Configuration and Composition of Machine Learning Algorithms (AutoML 2017), pp. 97–104, 2017.

2016

Post, Martijn J; van der Putten, Peter; van Rijn, J N

Does Feature Selection Improve Classification? A Large Scale Experiment in OpenML Inproceedings

In: Advances in Intelligent Data Analysis XV, pp. 158–170, Springer 2016.

van Rijn, J N

Massively Collaborative Machine Learning PhD Thesis

Leiden University, 2016.

2015

Vanschoren, J; van Rijn, J; Bischl, B; Casalicchio, G; Lang, M; Feurer, M

OpenML: a Networked Science Platform for Machine Learning (Abstract) Inproceedings

In: ICML 2015 MLOSS Workshop, 2015.

Vanschoren, J; van Rijn, J N; Bischl, B

Taking machine learning research online with OpenML Inproceedings

In: Proceedings of the 4th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, pp. 1–4, 2015.

van Rijn, J N; Takes, F W; Vis, J K

The Complexity of Rummikub Problems Inproceedings

In: BNAIC 2015: Proceedings of the 27th Benelux Conference on Artificial Intelligence, 2015.

van Rijn, J N; Holmes, G; Pfahringer, B; Vanschoren, J

Case study on bagging stable classifiers for data streams Inproceedings

In: BENELEARN 2015, 2015.

van Rijn, J N; Vanschoren, J

Sharing RapidMiner Workflows and Experiments with OpenML Inproceedings

In: Vanschoren, Joaquin; Brazdil, Pavel; Giraud-Carrier, Christophe; Kotthoff, Lars (Ed.): Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection (MetaSel), pp. 93–103, Aachen, 2015.

van Rijn, J N; Holmes, G; Pfahringer, B; Vanschoren, J

Having a Blast: Meta-Learning and Heterogeneous Ensembles for Data Streams Inproceedings

In: Data Mining (ICDM), 2015 IEEE International Conference on, pp. 1003–1008, IEEE 2015.

van Rijn, J N; Abdulrahman, S M; Brazdil, P; Vanschoren, J

Fast algorithm selection using learning curves Inproceedings

In: Advances in Intelligent Data Analysis XIV, pp. 298–309, Springer 2015.

2014

Hoogeboom, H J; Kosters, W A; van Rijn, J N; Vis, J K

Acyclic Constraint Logic and Games Journal Article

In: ICGA Journal, 37 (1), pp. 3–16, 2014.

Vanschoren, J; van Rijn, J N; Bischl, B; Torgo, L

OpenML: networked science in machine learning Journal Article

In: ACM SIGKDD Explorations Newsletter, 15 (2), pp. 49–60, 2014.

van Rijn, J N; Holmes, G; Pfahringer, B; Vanschoren, J

Towards meta-learning over data streams Inproceedings

In: MetaSel 2014, pp. 37–38, CEUR-WS 2014.

van Rijn, J N; Vis, J K

Endgame Analysis of Dou Shou Qi Journal Article

In: ICGA Journal, 37 (2), pp. 120–124, 2014.

van Rijn, J N; Holmes, G; Pfahringer, B; Vanschoren, J

Algorithm Selection on Data Streams Incollection

In: Discovery Science, 8777 , pp. 325–336, Springer, 2014.

2013

van Rijn, J N; Vis, J K

Complexity and retrograde analysis of the game Dou Shou Qi Inproceedings

In: BNAIC 2013: Proceedings of the 25th Benelux Conference on Artificial Intelligence, Delft University of Technology (TU Delft); under the auspices of the Benelux Association for Artificial Intelligence (BNVKI) and the Dutch Research School for Information and Knowledge Systems (SIKS) 2013.

van Rijn, J N; Umaashankar, V; Fischer, S; Bischl, B; Torgo, L; Gao, B; Winter, P; Wiswedel, B; Berthold, M R; Vanschoren, J

A RapidMiner extension for open machine learning Inproceedings

In: RapidMiner Community Meeting and Conference, pp. 59–70, 2013.

van Rijn, J N; Bischl, B; Torgo, L; Gao, B; Umaashankar, V; Fischer, S; Winter, P; Wiswedel, B; Berthold, M R; Vanschoren, J

OpenML: A Collaborative Science Platform Incollection

In: Machine Learning and Knowledge Discovery in Databases, pp. 645–649, Springer, 2013.