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Johannes Fürnkranz
2010 – today
- 2013
[j26]Eyke Hüllermeier, Johannes Fürnkranz: Editorial: Preference learning and ranking. Machine Learning 93(2-3): 185-189 (2013)- [e5]Johannes Fürnkranz, Eyke Hüllermeier, Tomoyuki Higuchi (Eds.): Discovery Science - 16th International Conference, DS 2013, Singapore, October 6-9, 2013. Proceedings. Lecture Notes in Computer Science 8140, Springer 2013, ISBN 978-3-642-40896-0
- 2012
- [b1]Johannes Fürnkranz, Dragan Gamberger, Nada Lavrac: Foundations of Rule Learning. Cognitive Technologies, Springer 2012, ISBN 978-3-540-75196-0, pp. 1-298
- [j25]Sang-Hyeun Park, Johannes Fürnkranz: Efficient prediction algorithms for binary decomposition techniques. Data Min. Knowl. Discov. 24(1): 40-77 (2012)
- [j24]Johannes Fürnkranz, Eyke Hüllermeier, Weiwei Cheng, Sang-Hyeun Park: Preference-based reinforcement learning: a formal framework and a policy iteration algorithm. Machine Learning 89(1-2): 123-156 (2012)
- [c55]Johannes Fürnkranz, Sang-Hyeun Park: Error-Correcting Output Codes as a Transformation from Multi-Class to Multi-Label Prediction. Discovery Science 2012: 254-267
- [c54]Wouter Duivesteijn, Eneldo Loza Mencía, Johannes Fürnkranz, Arno J. Knobbe: Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns. IDA 2012: 114-125
- [c53]Heiko Paulheim, Johannes Fürnkranz: Unsupervised generation of data mining features from linked open data. WIMS 2012: 31
- 2011
- [j23]Lars Wohlrab, Johannes Fürnkranz: A review and comparison of strategies for handling missing values in separate-and-conquer rule learning. J. Intell. Inf. Syst. 36(1): 73-98 (2011)
- [c52]
- [c51]
- [c50]Jan-Nikolas Sulzmann, Johannes Fürnkranz: Rule Stacking: An Approach for Compressing an Ensemble of Rule Sets into a Single Classifier. Discovery Science 2011: 323-334
- [c49]Frederik Janssen, Johannes Fürnkranz: Heuristic Rule-Based Regression via Dynamic Reduction to Classification. IJCAI 2011: 1330-1335
- [c48]Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier, Sang-Hyeun Park: Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning. ECML/PKDD (1) 2011: 312-327
- 2010
- [j22]Marco Ghiglieri, Johannes Fürnkranz: Learning to Recognize Missing E-Mail Attachments. Applied Artificial Intelligence 24(5): 443-462 (2010)
- [j21]Johannes Fürnkranz, Arno J. Knobbe: Guest Editorial: Global modeling using local patterns. Data Min. Knowl. Discov. 21(1): 1-8 (2010)
- [j20]Eneldo Loza Mencía, Sang-Hyeun Park, Johannes Fürnkranz: Efficient voting prediction for pairwise multilabel classification. Neurocomputing 73(7-9): 1164-1176 (2010)
- [j19]Eyke Hüllermeier, Johannes Fürnkranz: On predictive accuracy and risk minimization in pairwise label ranking. J. Comput. Syst. Sci. 76(1): 49-62 (2010)
- [j18]Frederik Janssen, Johannes Fürnkranz: On the quest for optimal rule learning heuristics. Machine Learning 78(3): 343-379 (2010)
- [j17]Johannes Fürnkranz, Jan Frederik Sima: On exploiting hierarchical label structure with pairwise classifiers. SIGKDD Explorations 12(2): 21-25 (2010)
- [c47]Sang-Hyeun Park, Lorenz Weizsäcker, Johannes Fürnkranz: Exploiting Code Redundancies in ECOC. Discovery Science 2010: 266-280
- [c46]Eneldo Loza Mencía, Johannes Fürnkranz: Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain. Semantic Processing of Legal Texts 2010: 192-215
- [p3]
- [p2]Nada Lavrac, Johannes Fürnkranz, Dragan Gamberger: Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms. Advances in Machine Learning I 2010: 121-146
- [e4]Johannes Fürnkranz, Thorsten Joachims (Eds.): Proceedings of the 27th International Conference on Machine Learning (ICML-10), June 21-24, 2010, Haifa, Israel. Omnipress 2010, ISBN 978-1-60558-907-7
- [r7]
- [r6]Johannes Fürnkranz: Decision Lists and Decision Trees. Encyclopedia of Machine Learning 2010: 261-262
- [r5]
- [r4]Johannes Fürnkranz: Machine Learning and Game Playing. Encyclopedia of Machine Learning 2010: 633-637
- [r3]Johannes Fürnkranz, Eyke Hüllermeier: Preference Learning. Encyclopedia of Machine Learning 2010: 789-795
- [r2]
- [r1]
2000 – 2009
- 2009
- [c45]Jan-Nikolas Sulzmann, Johannes Fürnkranz: An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules. Discovery Science 2009: 317-331
- [c44]Eneldo Loza Mencía, Sang-Hyeun Park, Johannes Fürnkranz: Efficient voting prediction for pairwise multilabel classification. ESANN 2009
- [c43]Immanuel Schweizer, Kamill Panitzek, Sang-Hyeun Park, Johannes Fürnkranz: An Exploitative Monte-Carlo Poker Agent. KI 2009: 65-72
- [c42]Sang-Hyeun Park, Johannes Fürnkranz: Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification. ECML/PKDD (2) 2009: 189-204
- [c41]Johannes Fürnkranz, Eyke Hüllermeier, Stijn Vanderlooy: Binary Decomposition Methods for Multipartite Ranking. ECML/PKDD (1) 2009: 359-374
- [c40]Frederik Janssen, Johannes Fürnkranz: A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. SDM 2009: 329-340
- 2008
- [j16]Eyke Hüllermeier, Johannes Fürnkranz, Weiwei Cheng, Klaus Brinker: Label ranking by learning pairwise preferences. Artif. Intell. 172(16-17): 1897-1916 (2008)
- [j15]Sacha Droste, Johannes Fürnkranz: Learning the Piece Values for Three Chess Variants. ICGA Journal 31(4): 209-233 (2008)
- [j14]Johannes Fürnkranz, Eyke Hüllermeier, Eneldo Loza Mencía, Klaus Brinker: Multilabel classification via calibrated label ranking. Machine Learning 73(2): 133-153 (2008)
- [c39]Frederik Janssen, Johannes Fürnkranz: An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics. Discovery Science 2008: 40-51
- [c38]Eneldo Loza Mencía, Johannes Fürnkranz: Pairwise learning of multilabel classifications with perceptrons. IJCNN 2008: 2899-2906
- [c37]Frederik Janssen, Johannes Fürnkranz: A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. LWA 2008: 42-49
- [c36]Jan-Nikolas Sulzmann, Johannes Fürnkranz: A Comparison of Techniques for Selecting and Combining Class Association Rules. LWA 2008: 87-93
- [c35]Eneldo Loza Mencía, Johannes Fürnkranz: Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain. ECML/PKDD (2) 2008: 50-65
- [c34]Dragan Gamberger, Nada Lavrac, Johannes Fürnkranz: Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach. PRICAI 2008: 636-645
- 2007
- [c33]Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyke Hüllermeier: On Pairwise Naive Bayes Classifiers. ECML 2007: 371-381
- [c32]Eyke Hüllermeier, Johannes Fürnkranz: On Minimizing the Position Error in Label Ranking. ECML 2007: 583-590
- [c31]
- [c30]
- [c29]Eneldo Loza Mencía, Johannes Fürnkranz: An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain. LWA 2007: 126-132
- [c28]
- 2006
- [j13]Michael H. Bowling, Johannes Fürnkranz, Thore Graepel, Ron Musick: Machine learning and games. Machine Learning 63(3): 211-215 (2006)
- [c27]Klaus Brinker, Johannes Fürnkranz, Eyke Hüllermeier: A Unified Model for Multilabel Classification and Ranking. ECAI 2006: 489-493
- [c26]Frederik Janssen, Johannes Fürnkranz: On Trading Off Consistency and Coverage in Inductive Rule Learning. LWA 2006: 306-313
- [e3]Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou (Eds.): Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings. Lecture Notes in Computer Science 4212, Springer 2006, ISBN 3-540-45375-X
- [e2]Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou (Eds.): Knowledge Discovery in Databases: PKDD 2006, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006, Proceedings. Lecture Notes in Computer Science 4213, Springer 2006, ISBN 3-540-45374-1
- 2005
- [j12]
- [j11]Johannes Fürnkranz, Peter A. Flach: ROC 'n' Rule Learning-Towards a Better Understanding of Covering Algorithms. Machine Learning 58(1): 39-77 (2005)
- [c25]Hervé Utard, Johannes Fürnkranz: Link-Local Features for Hypertext Classification. EWMF/KDO 2005: 51-64
- [c24]Eyke Hüllermeier, Johannes Fürnkranz: Learning Label Preferences: Ranking Error Versus Position Error. IDA 2005: 180-191
- [c23]Eyke Hüllermeier, Johannes Fürnkranz, Jürgen Beringer: On Position Error and Label Ranking through Iterated Choice. LWA 2005: 158-163
- [p1]
- [e1]Mathias Bauer, Boris Brandherm, Johannes Fürnkranz, Gunter Grieser, Andreas Hotho, Andreas Jedlitschka, Alexander Kröner (Eds.): Lernen, Wissensentdeckung und Adaptivität (LWA) 2005, GI Workshops, Saarbrücken, October 10th-12th, 2005. DFKI 2005
- 2004
- [c22]Johannes Fürnkranz: From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms. Local Pattern Detection 2004: 20-38
- [c21]Johannes Fürnkranz, Peter A. Flach: An Analysis of Stopping and Filtering Criteria for Rule Learning. ECML 2004: 123-133
- [c20]
- 2003
- [j10]
- [c19]
- [c18]
- [c17]
- 2002
- [j9]Johannes Fürnkranz, Christian Holzbaur, Robert Temel: User Profiling for the MELVIL Knowledge Retrieval System. Applied Artificial Intelligence 16(4): 243-281 (2002)
- [j8]Johannes Fürnkranz: Hyperlink ensembles: a case study in hypertext classification. Information Fusion 3(4): 299-312 (2002)
- [j7]Johannes Fürnkranz: Round Robin Classification. Journal of Machine Learning Research 2: 721-747 (2002)
- [c16]Johannes Fürnkranz: A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning. ALT 2002: 263-277
- [c15]
- 2001
- [c14]
- [c13]
- [c12]Hendrik Blockeel, Johannes Fürnkranz, Alexia Prskawetz, Francesco C. Billari: Detecting Temporal Change in Event Sequences: An Application to Demographic Data. PKDD 2001: 29-41
- 2000
- [j6]Klaus Kovar, Johannes Fürnkranz, Johann Petrak, Bernhard Pfahringer, Robert Trappl, Gerhard Widmer: Searching for Patterns in Political Event Sequences: Experiments with the Keds Database. Cybernetics and Systems 31(6): 649-668 (2000)
- [c11]Johannes Fürnkranz, Bernhard Pfahringer, Hermann Kaindl, Stefan Kramer: Learning to Use Operational Advice. ECAI 2000: 291-295
1990 – 1999
- 1999
- [j5]
- [c10]Johannes Fürnkranz: Exploiting Structural Information for Text Classification on the WWW. IDA 1999: 487-498
- 1998
- [j4]Johannes Fürnkranz, Bernhard Pfahringer: Guest Editorial: First-Order Knowledge Discovery in Databases. Applied Artificial Intelligence 12(5): 345-361 (1998)
- [j3]
- [i1]
- 1997
- [j2]Johannes Fürnkranz, Johann Petrak, Robert Trappl: Knowledge Discovery in International Conflict Databases. Applied Artificial Intelligence 11(2): 91-118 (1997)
- [j1]
- [c9]Franz-Günter Winkler, Johannes Fürnkranz: On Effort in AI Research: A Description Along Two Dimensions. Deep Blue Versus Kasparov: The Significance for Artificial Intelligence 1997: 56-62
- [c8]
- [c7]
- 1996
- [c6]Robert Trappl, Johannes Fürnkranz, Johann Petrak: Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases. ECAI 1996: 453-457
- 1995
- [c5]Johannes Fürnkranz: A Tight Integration of Pruning and Learning (Extended Abstract). ECML 1995: 291-294
- 1994
- [c4]
- [c3]
- [c2]
- [c1]Johannes Fürnkranz: A Comparison of Pruning Methods for Relational Concept Learning. KDD Workshop 1994: 371-382
Coauthor Index
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last updated on 2013-10-02 11:03 CEST by the dblp team