Johannes Fürnkranz

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Eyke HüllermeierProfessor of Computer Science, Paderborn UniversityVerified email at upb.de
Loza Mencía, EneldoKnowledge Engineering Group, TU DarmstadtVerified email at eneldo.net
Nada LavracJozef Stefan InstituteVerified email at ijs.si
Frederik JanssenTU DarmstadtVerified email at ke.tu-darmstadt.de
Jinseok NamAmazon Alexa AIVerified email at amazon.com
Christian WirthAI Engineer, Continental Automotive GmbHVerified email at christianwirth.net
Tomáš KliegrVysoká škola ekonomická v PrazeVerified email at vse.cz
Weiwei ChengSenior Principal Scientist at ZalandoVerified email at zalando.de
Johann PetrakAustrian Research Institute for Artificial Intelligence (OFAI)Verified email at sheffield.ac.uk
Michael RappLudwig-Maximilians-University MunichVerified email at ifi.lmu.de
Peter FlachProfessor of Artificial Intelligence, Department of Computer Science, University of BristolVerified email at bristol.ac.uk
Arno KnobbeLIACS, Leiden UniversityVerified email at liacs.leidenuniv.nl
Iryna GurevychFull Professor, TU Darmstadt; Adjunct Professor, MBZUAI, UAE; Affiliated Professor, INSAIT, BulgariaVerified email at cs.tu-darmstadt.de
Markus ZopfTU Darmstadt, GermanyVerified email at ke.tu-darmstadt.de
Gerhard WidmerProfessor of Computer Science, Johannes Kepler University LinzVerified email at jku.at
Gerhard NeumannProfessor, Karlsruhe Institute of Technology (KIT)Verified email at robot-learning.de
Timo BertramJohannes Kepler University LinzVerified email at faw.jku.at
Heiko PaulheimProfessor for Data Science at University of Mannheim, GermanyVerified email at informatik.uni-mannheim.de
Francesco C. BillariProfessor of Demography, Bocconi UniversityVerified email at unibocconi.it
Alexia Fürnkranz-PrskawetzProfessor of Mathematical Economics, Vienna University of TechnologyVerified email at econ.tuwien.ac.at

Johannes Fürnkranz

Johannes Kepler University, Linz

Verified email at faw.jku.at - Homepage

Interpretability Preference Learning Rule Learning Multilabel Classification Game Playing


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Multilabel classification via calibrated label ranking J Fürnkranz, E Hüllermeier, E Loza Mencía, K Brinker Machine learning 73, 133-153, 2008	1154	2008
Preference learning J Fürnkranz, E Hüllermeier Preference learning, 2011	943*	2011
Separate-and-conquer rule learning J Fürnkranz Artificial Intelligence Review 13, 3-54, 1999	791	1999
Foundations of Rule Learning J Fürnkranz, D Gamberger, N Lavrac Springer-Verlag, 2012	763*	2012
Label ranking by learning pairwise preferences E Hüllermeier, J Fürnkranz, W Cheng, K Brinker Artificial Intelligence 172 (16-17), 1897-1916, 2008	744	2008
Round robin classification J Fürnkranz Journal of Machine Learning Research 2 (Mar), 721-747, 2002	689	2002
Incremental reduced error pruning J Fürnkranz, G Widmer Proceedings of the International Conference on Machine Learning, 70-77, 1994	602	1994
Large-scale multi-label text classification—revisiting neural networks J Nam, J Kim, EL Mencía, I Gurevych, J Fürnkranz European Conference on Machine learning and Knowledge Discovery in Databases …, 2014	512	2014
A survey of preference-based reinforcement learning methods C Wirth, R Akrour, G Neumann, J Fürnkranz Journal of Machine Learning Research 18 (136), 1-46, 2017	456	2017
A study using n-gram features for text categorization J Fürnkranz Austrian Research Institute for Artifical Intelligence 3 (1998), 1-10, 1998	375	1998
Pairwise preference learning and ranking J Fürnkranz, E Hüllermeier European conference on machine learning, 145-156, 2003	340	2003
Roc ‘n’rule learning—towards a better understanding of covering algorithms J Fürnkranz, PA Flach Machine learning 58, 39-77, 2005	328	2005
Proceedings of the 27th international conference on machine learning (ICML-10) J Fürnkranz, T Joachims	311*	2010
Efficient pairwise multilabel classification for large-scale problems in the legal domain E Loza Mencía, J Fürnkranz Joint European conference on machine learning and knowledge discovery in …, 2008	237	2008
Maximizing subset accuracy with recurrent neural networks in multi-label classification J Nam, E Loza Mencía, HJ Kim, J Fürnkranz Advances in neural information processing systems 30, 2017	228	2017
Unsupervised generation of data mining features from linked open data H Paulheim, J Fümkranz Proceedings of the 2nd international conference on web intelligence, mining …, 2012	211	2012
Pruning algorithms for rule learning J Fürnkranz Machine learning 27, 139-172, 1997	203	1997
Exploiting structural information for text classification on the WWW J Fürnkranz International Symposium on Intelligent Data Analysis, 487-497, 1999	197	1999
An evaluation of grading classifiers AK Seewald, J Fürnkranz International symposium on intelligent data analysis, 115-124, 2001	195	2001
Preference-based reinforcement learning: a formal framework and a policy iteration algorithm J Fürnkranz, E Hüllermeier, W Cheng, SH Park Machine learning 89, 123-156, 2012	193	2012

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