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Johannes Fürnkranz
Título
Citado por
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Año
Multilabel classification via calibrated label ranking
J Fürnkranz, E Hüllermeier, E Loza Mencía, K Brinker
Machine learning 73, 133-153, 2008
11422008
Preference learning
J Fürnkranz, E Hüllermeier
Preference learning, 2011
914*2011
Separate-and-conquer rule learning
J Fürnkranz
Artificial Intelligence Review 13, 3-54, 1999
7811999
Label ranking by learning pairwise preferences
E Hüllermeier, J Fürnkranz, W Cheng, K Brinker
Artificial Intelligence 172 (16-17), 1897-1916, 2008
7412008
Round robin classification
J Fürnkranz
The Journal of Machine Learning Research 2, 721-747, 2002
6962002
Incremental reduced error pruning
J Fürnkranz, G Widmer
Proceedings of the International Conference on Machine Learning, 70-77, 1994
5971994
Foundations of Rule Learning
J Fürnkranz, D Gamberger, N Lavrac
Springer-Verlag, 2012
5742012
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
4992014
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
4172017
A study using n-gram features for text categorization
J Fürnkranz
Austrian Research Institute for Artifical Intelligence 3 (1998), 1-10, 1998
3761998
Pairwise preference learning and ranking
J Fürnkranz, E Hüllermeier
European conference on machine learning, 145-156, 2003
3372003
Roc ‘n’rule learning—towards a better understanding of covering algorithms
J Fürnkranz, PA Flach
Machine learning 58, 39-77, 2005
3222005
Proceedings of the 27th international conference on machine learning (ICML-10)
J Fürnkranz, T Joachims
293*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
2342008
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
2262017
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
2262012
Pruning algorithms for rule learning
J Fürnkranz
Machine learning 27, 139-172, 1997
2021997
An evaluation of grading classifiers
AK Seewald, J Fürnkranz
International symposium on intelligent data analysis, 115-124, 2001
2002001
Exploiting structural information for text classification on the WWW
J Fürnkranz
International Symposium on Intelligent Data Analysis, 487-497, 1999
1951999
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
1872012
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Artículos 1–20