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447 Publications


2015 | Conference Paper | LibreCat-ID: 10238
Dyad Ranking Using A Bilinear Plackett-Luce Model
D. Schäfer, E. Hüllermeier, in: In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 227–242.
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2015 | Conference Paper | LibreCat-ID: 10239
Superset Learning Based on Generalized Loss Minimization
E. Hüllermeier, W. Cheng, in: In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 260–275.
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2015 | Conference Paper | LibreCat-ID: 10240
Weighted Rank Correlation : A Flexible Approach Based on Fuzzy Order Relations
S. Henzgen, E. Hüllermeier, in: In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 422–437.
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2015 | Conference Paper | LibreCat-ID: 10241
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach
B. Szörényi, R. Busa-Fekete, A. Paul, E. Hüllermeier, in: In Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015, pp. 604–612.
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2015 | Conference Paper | LibreCat-ID: 10242
Online F-Measure Optimization
B. Szörényi, R. Busa-Fekete, K. Dembczynski, E. Hüllermeier, in: In Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015, pp. 595–603.
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2015 | Conference Paper | LibreCat-ID: 10243
A CBR Approach to the Angry Birds Game
A. El Mesaoudi-Paul, E. Hüllermeier, in: In Workshop Proc. 23rd International Conference on Case-Based Reasoning (ICCBR 2015), 2015, pp. 68–77.
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2015 | Conference Paper | LibreCat-ID: 10244
Preference-Based Meta- Learning Using Dyad Ranking: Recommending Algorithms in Cold-Start Situations
D. Schäfer, E. Hüllermeier, in: In Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection (MetaSel@PKDD/ECML), 2015, pp. 110–111.
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2015 | Conference Paper | LibreCat-ID: 10245
Locally weighted regression through data imprecisiation
S. Lu, E. Hüllermeier, in: Proceedings 25. Workshop Computational Intelligence, 2015, pp. 97–104.
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2015 | Conference Paper | LibreCat-ID: 10246
Depth estimation in monocular images: Quantitative versus qualitative approaches
R. Ewerth, A. Balz, J. Gehlhaar, K. Dembczynski, E. Hüllermeier, in: Proceedings 25. Workshop Computational Intelligence, 2015, pp. 235–240.
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2015 | Journal Article | LibreCat-ID: 10319
On the Bayes-Optimality of F-Measure Maximizers
W. Waegeman, K. Dembczynski, A. Jachnik, W. Cheng, E. Hüllermeier, In Journal of Machine Learning Research 15 (2015) 3333–3388.
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2015 | Journal Article | LibreCat-ID: 10320
Does machine learning need fuzzy logic?
E. Hüllermeier, Fuzzy Sets and Systems 281 (2015) 292–299.
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2015 | Journal Article | LibreCat-ID: 10321 LibreCat
 

2015 | Journal Article | LibreCat-ID: 10322 LibreCat
 

2015 | Journal Article | LibreCat-ID: 10323
Overlap Indices: Construction of and Application of Interpolative Fuzzy Systems
S. Garcia-Jimenez, U. Bustince, E. Hüllermeier, R. Mesiar, N.R. Pal, A. Pradera, IEEE Transactions on Fuzzy Systems 23 (2015) 1259–1273.
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2015 | Journal Article | LibreCat-ID: 10324
Fast Fuzzy Pattern Tree Learning of Classification
R. Senge, E. Hüllermeier, IEEE Transactions on Fuzzy Systems 23 (2015) 2024–2033.
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2014 | Journal Article | LibreCat-ID: 16046
Preference-based learning of ideal solutions in TOPSIS-like decision models
M. Agarwal, A. Fallah Tehrani, E. Hüllermeier, Journal of Multi-Criteria Decision Analysis 22 (2014).
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2014 | Journal Article | LibreCat-ID: 16060
Extended graph-based models for enhanced similarity search in Cabase
T. Krotzky, T. Fober, E. Hüllermeier, G. Klebe, IEEE/ACM Transactions of Computational Biology and Bioinformatics 11 (2014) 878–890.
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2014 | Journal Article | LibreCat-ID: 16064
Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization
E. Hüllermeier, International Journal of Approximate Reasoning 55 (2014) 1519–1534.
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2014 | Journal Article | LibreCat-ID: 16069
Visualization of evolving fuzzy-rule-based systems
S. Henzgen, M. Strickert, E. Hüllermeier, Evolving Systems 5 (2014) 175–191.
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2014 | Journal Article | LibreCat-ID: 16077
Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm.
R. Busa-Fekete, B. Szörenyi, P. Weng, W. Cheng, E. Hüllermeier, Machine Learning 97 (2014) 327–351.
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