Jan van Rijn
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Jan N. van Rijn,
a Dutch computer scientist and assistant professor at Leiden University, where he already defended his Ph.D. thesis in 2016 on massively collaborative machine learning [2], and at LIACS, his Master's thesis in 2012 on game complexity, [3] of Klondike, Mahjong, Nonogram and Dou Shou Qi (Jungle, Jungle Chess, Animals Chess) [4]. His research interests further include retrograde analysis, machine learning, and meta learning along with massively collaborative data mining, where data mining efforts are distributed to multiple collaborating agents - human or software.
Selected Publications
- Jan van Rijn (2012). Playing Games: The complexity of Klondike, Mahjong, Nonograms and Animal Chess. Master's thesis, Leiden Institute of Advanced Computer Science, pdf
- Jan van Rijn, Joaquin Vanschoren (2013). OpenML: An Open Science Platform for Machine Learning. BENELearn 2013 [6]
- Jan van Rijn, Jonathan K. Vis (2013). Complexity and Retrograde Analysis of the Game Dou Shou Qi. BNAIC 2013
- Hendrik Jan Hoogeboom, Walter Kosters, Jan van Rijn, Jonathan K. Vis (2014, 2016). Acyclic Constraint Logic and Games. ICGA Journal, Vol 37, No. 1, arXiv:1604.05487
- Jan van Rijn, Geoffrey Holmes, Bernhard Pfahringer, Joaquin Vanschoren (2014). Algorithm Selection on Data Streams. DS 2014
- Jan van Rijn, Geoffrey Holmes, Bernhard Pfahringer, Joaquin Vanschoren (2014). Towards Meta-learning over Data Streams. MetaSel 2014
- Jan van Rijn, Jonathan K. Vis (2014). Endgame Analysis of Dou Shou Qi. ICGA Journal, Vol. 37, No. 2, pdf
- Jan van Rijn (2016). Massively collaborative machine learning. Ph.D. thesis, Leiden University
External Links
References
- ↑ Jan N. van Rijn - LIACS
- ↑ Jan van Rijn (2016). Massively collaborative machine learning. Ph.D. thesis, Leiden University
- ↑ Jan van Rijn (2012). Playing Games: The complexity of Klondike, Mahjong, Nonograms and Animal Chess. Master's thesis, Leiden Institute of Advanced Computer Science, pdf
- ↑ Jungle (board game) from Wikipedia
- ↑ dblp: Jan N. van Rijn
- ↑ OpenML.org