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418 Publications


2016 | Book Chapter | LibreCat-ID: 10214
J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia of Machine Learning and Data Mining, C. Sammut and G. I. Webb, Eds. Springer, 2016.
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2016 | Conference (Editor) | LibreCat-ID: 10221
F. Hoffmann, E. Hüllermeier, and R. Mikut, Eds., Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany. 2016.
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2016 | Conference Paper | LibreCat-ID: 10226
K. Pfannschmidt, E. Hüllermeier, S. Held, and R. Neiger, “Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts,” in In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, 2016, pp. 450–461.
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2016 | Journal Article | LibreCat-ID: 10264
M. Leinweber et al., “CavSimBase: A database for large scale comparison of protein binding sites,” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 6, pp. 1423–1434, 2016.
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2016 | Dissertation | LibreCat-ID: 141
F. Mohr, Towards Automated Service Composition Under Quality Constraints. Universität Paderborn, 2016.
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2016 | Conference Paper | LibreCat-ID: 15404
D. Schäfer and E. Hüllermeier, “Plackett-Luce networks for dyad ranking,” in in Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany, 2016.
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2016 | Journal Article | LibreCat-ID: 16041
M. Leinweber et al., “CavSimBase: A database for large scale comparison of protein binding sites,” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 6, pp. 1423–1434, 2016.
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2016 | Conference Paper | LibreCat-ID: 184
V. Melnikov and E. Hüllermeier, “Learning to Aggregate Using Uninorms,” in Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–771.
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2016 | Conference Paper | LibreCat-ID: 10222
K. Jasinska, K. Dembczynski, R. Busa-Fekete, T. Klerx, and E. Hüllermeier, “Extreme F-measure maximization using sparse probability estimates ,” in Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA, 2016.
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2016 | Conference Paper | LibreCat-ID: 10227
C. Labreuche, E. Hüllermeier, P. Vojtas, and A. Fallah Tehrani, “On the Identifiability of models in multi-criteria preference learning ,” in Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.
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2016 | Conference Paper | LibreCat-ID: 15400
C. Labreuche, E. Hüllermeier, P. Vojtas, and A. Fallah Tehrani, “On the identifiability of models  in multi-criteria preference learning,” in in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, 2016.
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2016 | Journal Article | LibreCat-ID: 3318
V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, and Pritha Gupta, “Pairwise versus Pointwise Ranking: A Case Study,” Schedae Informaticae, vol. 25, 2016.
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2015 | Journal Article | LibreCat-ID: 10324
R. Senge and E. Hüllermeier, “Fast Fuzzy Pattern Tree Learning of Classification,” IEEE Transactions on Fuzzy Systems, vol. 23, no. 6, pp. 2024–2033, 2015.
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2015 | Conference Paper | LibreCat-ID: 10235
F. Hoffmann and E. Hüllermeier, “Proceedings 25. Workshop Computational Intelligence KIT Scientific Publishing,” 2015.
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2015 | Conference Paper | LibreCat-ID: 10242
B. Szörényi, R. Busa-Fekete, K. Dembczynski, and E. Hüllermeier, “Online F-Measure Optimization,” in in Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015, pp. 595–603.
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2015 | Conference Paper | LibreCat-ID: 15406
D. Schäfer and E. Hüllermeier, “Preference-based meta-learning using dyad ranking: Recommending algorithms in cold-start situations,” in in Proceedings of the 2015 international Workshop on Meta-Learning and Algorithm Selection co-located ECML/PKDD, Porto, Portugal, 2015, pp. 110–111.
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2015 | Journal Article | LibreCat-ID: 16067
A. Shaker and E. Hüllermeier, “Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study,” Neurocomputing, vol. 150, pp. 250–264, 2015.
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2015 | Conference Paper | LibreCat-ID: 319
F. Mohr, A. Jungmann, and H. Kleine Büning, “Automated Online Service Composition,” in Proceedings of the 12th IEEE International Conference on Services Computing (SCC), 2015, pp. 57--64.
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2015 | Journal Article | LibreCat-ID: 4792
R. Senge and E. Hüllermeier, “Fast Fuzzy Pattern Tree Learning for Classification,” IEEE Transactions on Fuzzy Systems, vol. 23, no. 6, pp. 2024–2033, 2015.
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2015 | Conference Paper | LibreCat-ID: 10236
A. Abdel-Aziz and E. Hüllermeier, “Case Base Maintenance in Preference-Based CBR,” in In Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015), 2015, pp. 1–14.
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2015 | Conference Paper | LibreCat-ID: 10243
A. El Mesaoudi-Paul and E. Hüllermeier, “A CBR Approach to the Angry Birds Game,” in in Workshop Proc. 23rd International Conference on Case-Based Reasoning (ICCBR 2015), 2015, pp. 68–77.
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2015 | Journal Article | LibreCat-ID: 10320
E. Hüllermeier, “Does machine learning need fuzzy logic?,” Fuzzy Sets and Systems, vol. 281, pp. 292–299, 2015.
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2015 | Conference Paper | LibreCat-ID: 15750
R. Ewerth, A. Balz, J. Gehlhaar, K. Dembczynski, and E. Hüllermeier, “Depth estimation in monocular images: Quantitative versus qualitative approaches,” in In Proceedings 25. Workshop Computational Intelligence, Dortmund, Germany, 2015, pp. 235–240.
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2015 | Journal Article | LibreCat-ID: 16049
R. Senge and E. Hüllermeier, “Fast fuzzy pattern tree learning for classification ,” IEEE Transactions on Fuzzy Systems, vol. 23, no. 6, pp. 2024–2033, 2015.
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2015 | Journal Article | LibreCat-ID: 16051
E. Hüllermeier, “From knowledge-based to data driven fuzzy modeling: Development, criticism and alternative directions,” Informatik Spektrum, vol. 38, no. 6, pp. 500–509, 2015.
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2015 | Conference Paper | LibreCat-ID: 10237
B. Szörényi, R. Busa-Fekete, P. Weng, and E. Hüllermeier, “Qualitative Multi-Armed Bandits: A Quantile-Based Approach,” in In Proceedings International Conference on Machine Learning (ICML 2015), 2015, pp. 1660–1668.
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2015 | Conference Paper | LibreCat-ID: 10244
D. Schäfer and E. Hüllermeier, “Preference-Based Meta- Learning Using Dyad Ranking: Recommending Algorithms in Cold-Start Situations,” 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 | Journal Article | LibreCat-ID: 10319
W. Waegeman, K. Dembczynski, A. Jachnik, W. Cheng, and E. Hüllermeier, “On the Bayes-Optimality of F-Measure Maximizers,” in Journal of Machine Learning Research, vol. 15, pp. 3333–3388, 2015.
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2015 | Journal Article | LibreCat-ID: 10321
A. Shaker and E. Hüllermeier, “Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study,” Neurocomputing, vol. 150, pp. 250–264, 2015.
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2015 | Conference Paper | LibreCat-ID: 15749
A. Paul and E. Hüllermeier, “A cbr approach to the angry birds game,” in In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany, 2015, pp. 68–77.
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2015 | Conference Paper | LibreCat-ID: 15751
S. Lu and E. Hüllermeier, “Locally weighted regression through data imprecisiation,” in in Proceedings 25th Workshop Computational Intelligence, Dortmund Germany, 2015, pp. 97–104.
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2015 | Journal Article | LibreCat-ID: 323
A. Jungmann and F. Mohr, “An approach towards adaptive service composition in markets of composed services,” Journal of Internet Services and Applications, no. 1, pp. 1–18, 2015.
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2015 | Conference Paper | LibreCat-ID: 10238
D. Schäfer and E. Hüllermeier, “Dyad Ranking Using A Bilinear Plackett-Luce Model,” 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: 10240
S. Henzgen and E. Hüllermeier, “Weighted Rank Correlation : A Flexible Approach Based on Fuzzy Order Relations,” 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: 10245
S. Lu and E. Hüllermeier, “Locally weighted regression through data imprecisiation,” in Proceedings 25. Workshop Computational Intelligence, 2015, pp. 97–104.
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2015 | Journal Article | LibreCat-ID: 10322
E. Hüllermeier, “From Knowledge-based to Data-driven fuzzy modeling-Development, criticism and alternative directions,” Informatik Spektrum, vol. 38, no. 6, pp. 500–509, 2015.
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2015 | Journal Article | LibreCat-ID: 16053
E. Hüllermeier, “Does machine learning need fuzzy logic?,” Fuzzy Sets and Systems, vol. 281, pp. 292–299, 2015.
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2015 | Journal Article | LibreCat-ID: 16058
W. Waegeman, K. Dembczynski, A. Jachnik, W. Cheng, and E. Hüllermeier, “On the Bayes-optimality of F-measure maximizers,” Journal of Machine Learning Research, vol. 15, pp. 3313–3368, 2015.
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2015 | Conference Paper | LibreCat-ID: 280
S. Arifulina, M. C. Platenius, F. Mohr, G. Engels, and W. Schäfer, “Market-Specific Service Compositions: Specification and Matching,” in Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet, 2015, pp. 333--340.
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2015 | Conference Paper | LibreCat-ID: 324
F. Mohr, “A Metric for Functional Reusability of Services,” in Proceedings of the 14th International Conference on Software Reuse (ICSR), 2015, pp. 298--313.
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2015 | Journal Article | LibreCat-ID: 10323
S. Garcia-Jimenez, U. Bustince, E. Hüllermeier, R. Mesiar, N. R. Pal, and A. Pradera, “Overlap Indices: Construction of and Application of Interpolative Fuzzy Systems,” IEEE Transactions on Fuzzy Systems, vol. 23, no. 4, pp. 1259–1273, 2015.
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2015 | Conference Paper | LibreCat-ID: 10234
E. Hüllermeier and M. Minor, “Case-Based Reasoning Research and Development ,” in in Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015) LNAI 9343, 2015.
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2015 | Conference Paper | LibreCat-ID: 10239
E. Hüllermeier and W. Cheng, “Superset Learning Based on Generalized Loss Minimization ,” 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: 10241
B. Szörényi, R. Busa-Fekete, A. Paul, and E. Hüllermeier, “Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach,” in in Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015, pp. 604–612.
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2015 | Conference Paper | LibreCat-ID: 10246
R. Ewerth, A. Balz, J. Gehlhaar, K. Dembczynski, and E. Hüllermeier, “Depth estimation in monocular images: Quantitative versus qualitative approaches,” in Proceedings 25. Workshop Computational Intelligence, 2015, pp. 235–240.
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2014 | Journal Article | LibreCat-ID: 10297
F. Hoffmann, E. Hüllermeier, and A. Kroll, “Ausgewählte Beiträge des GMA-Fachausschusses 5.14,” Computational Intelligence Automatisierungstechnik, vol. 62, no. 10, pp. 685–686, 2014.
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2014 | Journal Article | LibreCat-ID: 10312
M. Mernberger, M. Moog, S. Stork, S. Zauner, U. G. Maier, and E. Hüllermeier, “Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances,” J. Bioinformatics and Computational Biology, vol. 12, no. 1, 2014.
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2014 | Journal Article | LibreCat-ID: 10317
T. Krotzky, T. Fober, E. Hüllermeier, and G. Klebe, “Extended Graph-Based Models for Enhanced Similarity Search in Cavbase,” IEEE/ACM Trans. Comput. Biology Bioinform., vol. 11, no. 5, pp. 878–890, 2014.
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2014 | Conference Paper | LibreCat-ID: 10247
R. Busa-Fekete, B. Szörényi, and E. Hüllermeier, “PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences,” in Proceedings AAAI 2014, Quebec, Canada, 2014, pp. 1701–1707.
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2014 | Conference Paper | LibreCat-ID: 10254
T. Calders, F. Esposito, E. Hüllermeier, and R. Meo, “Machine Learning and Knowledge Discovery in Databases-European Conf. ECML/PKDD, Nancy, France,” in Proceedings, Parts I-III. Lecture Notes in Computer Science, 2014, pp. 8724–8726.
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