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Shaker, Ammar, et al. “Learning TSK Fuzzy Rules from Data Streams.” Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.
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Bräuning, M., et al. “Lexicographic Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning Method with an Application  in Accounting.” European Journal of Operational Research, vol. 258, no. 1, 2017, pp. 295–306.
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Platenius, M. C., et al. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering, vol. 43, no. 8, 2017, pp. 739–59.
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Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy Rule-Based Systems: A Critical Reflection.” The Computing Research Repository  (CoRR), abs/1712.00646, 2017.
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Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stochastic Recursive Inclusion in Two Timescales with an Application to the Lagrangian Dual Problem.” Stochastics, vol. 88, no. 8, Taylor \'26; Francis, 2016, pp. 1173–87.
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Melnikov, Vitalik, et al. “Pairwise versus Pointwise Ranking: A Case Study.”10.4467/20838476si.16.006.6187__Schedae Informaticae, vol. 25, Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego, 2016, doi:10.4467/20838476si.16.006.6187.
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Platenius, Marie Christin, et al. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.”10.1109/TSE.2016.2632115__IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017, no. 8, IEEE, 2016, pp. 739–59, doi:10.1109/TSE.2016.2632115.
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Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms.”10.1007/978-3-319-46227-1_47__Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–71, doi:10.1007/978-3-319-46227-1_47.
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Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, Springer, 2016.
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Labreuche, C., et al. “On the Identifiability of Models  in Multi-Criteria Preference Learning.” In Proceedings DPL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, edited by R. Busa-Fekete et al., 2016.
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Schäfer, D., and Eyke Hüllermeier. “Preference -Based Reinforcement Learning Using Dyad Ranking.” In Proceedings DPL16 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany, edited by R. Busa-Fekete et al., 2016.
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Couso, Ines, et al. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” In Proceedings DPL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, edited by R. Busa-Fekete et al., 2016.
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Lu, S., and Eyke Hüllermeier. “Support Vector Classification on Noisy Data Using Fuzzy Superset Losses.” In Proceedings 26th Workshop Computational Intelligence, Dortmund Germany, edited by Eyke Hüllermeier et al., KIT Scientific Publishing, 2016, pp. 1–8.
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Schäfer, D., and Eyke Hüllermeier. “Plackett-Luce Networks for Dyad Ranking.” In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany, 2016.
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Pfannschmidt, Karlson, et al. “Evaluating Tests in Medical  Diagnosis-Combining Machine Learning with Game-Theoretical Concepts.” In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer, 2016, pp. 450–61.
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Leinweber, M., et al. “CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites.” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 6, 2016, pp. 1423–34.
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Mohr, Felix. Towards Automated Service Composition Under Quality Constraints. Universität Paderborn, 2016, doi:10.17619/UNIPB/1-171.
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Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, Springer, 2016.
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Hoffmann, F., et al., editors.  Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany. 2016.
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