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
Frederik JanssenTU DarmstadtVerified email at ke.tu-darmstadt.de
Jinseok NamAmazon Alexa AIVerified email at amazon.com
Nada LavracJozef Stefan InstituteVerified email at ijs.si
Christian WirthAI Engineer, Continental Automotive GmbHVerified email at christianwirth.net
Johann PetrakThe University of SheffieldVerified email at sheffield.ac.uk
Weiwei ChengSenior Principal Scientist at ZalandoVerified email at zalando.de
Michael RappLudwig-Maximilians-University MunichVerified email at ifi.lmu.de
Tomáš KliegrVysoká škola ekonomická v PrazeVerified email at vse.cz
Peter FlachProfessor of Artificial Intelligence, Department of Computer Science, University of BristolVerified email at bristol.ac.uk
Iryna GurevychFull Professor, TU Darmstadt; Adjunct Professor, MBZUAI, Abu DhabiVerified 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
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
Arno KnobbeLIACS, Leiden UniversityVerified email at liacs.leidenuniv.nl
Hyunwoo J. KimKorea UniversityVerified email at korea.ac.kr
Hien DangKnowledge Engineering Group, Technische Universität DarmstadtVerified email at ke.tu-darmstadt.de

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	1040	2008
Preference learning J Fürnkranz, E Hüllermeier Preference learning, 2011	845*	2011
Separate-and-conquer rule learning J Fürnkranz Artificial Intelligence Review 13, 3-54, 1999	772	1999
Label ranking by learning pairwise preferences E Hüllermeier, J Fürnkranz, W Cheng, K Brinker Artificial Intelligence 172 (16-17), 1897-1916, 2008	701	2008
Round robin classification J Fürnkranz The Journal of Machine Learning Research 2, 721-747, 2002	675	2002
Incremental reduced error pruning J Fürnkranz, G Widmer Proceedings of the International Conference on Machine Learning, 70-77, 1994	575	1994
Foundations of Rule Learning J Fürnkranz, D Gamberger, N Lavrac Springer-Verlag, 2012	510	2012
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	466	2014
A study using n-gram features for text categorization J Fürnkranz Austrian Research Institute for Artifical Intelligence 3 (1998), 1-10, 1998	366	1998
Roc ‘n’rule learning—towards a better understanding of covering algorithms J Fürnkranz, PA Flach Machine learning 58, 39-77, 2005	314	2005
Pairwise preference learning and ranking J Fürnkranz, E Hüllermeier European conference on machine learning, 145-156, 2003	305	2003
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	270	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	216	2012
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	211	2008
An evaluation of grading classifiers AK Seewald, J Fürnkranz International symposium on intelligent data analysis, 115-124, 2001	199	2001
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	194	2017
Exploiting structural information for text classification on the WWW J Fürnkranz International Symposium on Intelligent Data Analysis, 487-497, 1999	192	1999
Pruning algorithms for rule learning J Fürnkranz Machine learning 27, 139-172, 1997	183	1997
A case study in using linguistic phrases for text categorization on the WWW J Fürnkranz, T Mitchell, E Riloff Proceedings from the AAAI/ICML Workshop on Learning for Text Categorization …, 1998	180	1998
A unified model for multilabel classification and ranking K Brinker, J Fürnkranz, E Hüllermeier Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on …, 2006	175	2006

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