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Busa-Fekete, Robert, et al. “Preference-Based Evolutionary Optimization Using Generalized Racing Algorithms.” In Proceedings 23th Workshop Computational Intelligence, Dortmund Germany, edited by F. Hoffmann and Eyke Hüllermeier, KIT Scientific Publishing, 2013, pp. 237–46.
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Henzgen, S., and Eyke Hüllermeier. “Weighted Rank Correlation Measures Based on Fuzzy Order Relations.” In Proceedings 23th Workshop Computational Intelligence, Dortmund Germany, edited by F. Hoffmann and Eyke Hüllermeier, KIT Scientific Publishing, 2013, pp. 227–36.
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Cheng, W., and Eyke Hüllermeier. “A Nearest Neigbor Approach to Label Ranking Based on Generalized Labelwise Loss Minimization.” In Proceedings M-PREF, 7th Multidisciplinary Workshop on Advances in Preference Handling Beijing, China, 2013.
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Shaker, Ammar, and Eyke Hüllermeier. “Event History Analysis on Data Streams: An Application to Earthquake Occurence.” In Proceedings RealStream 2013, 1st International Workshop on Real-World Challenges for Data Stream Mining, Prague, Czech Republic, edited by G. Krempl et al., 2013, pp. 38–41.
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Fober, T., et al. “Local Clique Merging: An Extension of the Maximum Common Subgraph Measure with Applications in Structural Bioinformatics, Algorithms from and for Nature and Life.” In Proceedings GFKL-2011, Conference of the German Classification Society, Frankfurt Germany, edited by B. Lausen et al., Springer, 2013, pp. 279–86.
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Fallah Tehrani, A., and Eyke Hüllermeier. “Ordinal Choquistic Regression .” In Proceedings EUSFLAT-2013 8th International Conference on the European Society for Fuzzy Logic and Technology, Milano, Italy, edited by J. Montero et al., Atlantis Press, 2013.
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Nasiri, N., et al. “Fuzzy Pattern Trees as an Alternative to Rule-Based Fuzzy Systems: Knowledge-Driven, Data-Driven and Hybrid Modeling of Colour Yield in Poyester Dyeing, Edmonton, Canada.” In Proceedings IFSA-2013 World Congress of the International Fuzzy Systems Association, Edmonton, Canada, 2013, pp. 715–21.
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Haasenritter, J., et al. “Diagnose Im Kontext - Eine Erweiterte Perspektive.” Zeitschrift Für Evidenz, Fortbildung Und Qualität Im Gesundheitswesen (ZEFQ), vol. 107, 2013, pp. 585–91.
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Shaker, A., et al. “Evolving Fuzzy Pattern Trees for Binary Classification on Data Streams.” Information Sciences, vol. 220, 2013, pp. 34–45.
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Szarvas, G., et al. “Learning to Rank Lexical Substitutions.” In Proceedings EMNLP-2013 Conference on Empirical Methods in Natural Language Processing, Seattle, USA, 2013.
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Dembczynski, K., et al. “Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization.” In Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, edited by S. Dasgupta and D. McAllester, 2013, pp. 1130–38.
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Busa-Fekete, Robert, et al. “Top-k Selection Based on Adaptive Sampling of Noisy Preferences.” In Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, edited by S. Dasgupta and D. McAllester, 2013, pp. 1094–102.
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Hüllermeier, Eyke, and W. Cheng. “Preference-Based CBR: General Ideas and Basic Principles.” In Proceedings IJCAI-13, 23rd International Joint Conference on Artificial Intelligence, Beijing, China, edited by F. Rossi, AAAI Press, 2013, pp. 3012–16.
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