Ewerth, R., et al. “Depth Estimation in Monocular Images: Quantitative versus Qualitative Approaches.” In Proceedings 25. Workshop Computational Intelligence, Dortmund, Germany, edited by F. Hoffmann and Eyke Hüllermeier, KIT Scientific Publishing, 2015, pp. 235–40.

Lu, S., and Eyke Hüllermeier. “Locally Weighted Regression through Data Imprecisiation.” In Proceedings 25th Workshop Computational Intelligence, Dortmund Germany, edited by F. Hoffmann and Eyke Hüllermeier, KIT Scientific Publishing, 2015, pp. 97–104.

Senge, Robin, and Eyke Hüllermeier. “Fast Fuzzy Pattern Tree Learning for Classification .” IEEE Transactions on Fuzzy Systems, vol. 23, no. 6, 2015, pp. 2024–33.

Hüllermeier, Eyke. “From Knowledge-Based to Data Driven Fuzzy Modeling: Development, Criticism and Alternative Directions.” Informatik Spektrum, vol. 38, no. 6, 2015, pp. 500–09.

Hüllermeier, Eyke. “Does Machine Learning Need Fuzzy Logic?” Fuzzy Sets and Systems, vol. 281, 2015, pp. 292–99.

Waegeman, W., et al. “On the Bayes-Optimality of F-Measure Maximizers.” Journal of Machine Learning Research, vol. 15, 2015, pp. 3313–68.

Shaker, A., and Eyke Hüllermeier. “Recovery Analysis for Adaptive Learning from Non-Stationary Data Streams: Experimental Design and Case Study.” Neurocomputing, vol. 150, 2015, pp. 250–64.

Hüllermeier, Eyke, and M. Minor. “Case-Based Reasoning Research and Development .” In Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015) LNAI 9343, Springer, 2015.

Hoffmann, F., and Eyke Hüllermeier. Proceedings 25. Workshop Computational Intelligence KIT Scientific Publishing. 2015.

Abdel-Aziz, A., and Eyke Hüllermeier. “Case Base Maintenance in Preference-Based CBR.” In Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015), 2015, pp. 1–14.

Szörényi, B., et al. “Qualitative Multi-Armed Bandits: A Quantile-Based Approach.” In Proceedings International Conference on Machine Learning (ICML 2015), 2015, pp. 1660–68.

Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using A Bilinear Plackett-Luce Model.” In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 227–42.

Hüllermeier, Eyke, and W. Cheng. “Superset Learning Based on Generalized Loss Minimization .” In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 260–75.

Henzgen, Sascha, and Eyke Hüllermeier. “Weighted Rank Correlationf: A Flexible Approach Based on Fuzzy Order Relations.” In Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 2015, pp. 422–37.

Szörényi, B., et al. “Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach.” In Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015, pp. 604–12.

Szörényi, B., et al. “Online F-Measure Optimization.” In Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015, pp. 595–603.

El Mesaoudi-Paul, Adil, and Eyke Hüllermeier. “A CBR Approach to the Angry Birds Game.” In Workshop Proc. 23rd International Conference on Case-Based Reasoning (ICCBR 2015), 2015, pp. 68–77.

Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Meta- Learning Using Dyad Ranking: Recommending Algorithms in Cold-Start Situations.” In Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection (MetaSel@PKDD/ECML), 2015, pp. 110–11.

Lu, S., and Eyke Hüllermeier. “Locally Weighted Regression through Data Imprecisiation.” Proceedings 25. Workshop Computational Intelligence, 2015, pp. 97–104.

Ewerth, Ralph, et al. “Depth Estimation in Monocular Images: Quantitative versus Qualitative Approaches.” Proceedings 25. Workshop Computational Intelligence, 2015, pp. 235–40.