Henzgen, S., and Eyke Hüllermeier. “Weighted Rank Correlation Measures Based on Fuzzy Order Relations.” In In Proceedings 23th Workshop Computational Intelligence, Dortmund Germany, edited by F. Hoffmann and Eyke Hüllermeier, 227–36. KIT Scientific Publishing, 2013.

Weng, P., Robert Busa-Fekete, and Eyke Hüllermeier. “Interactive Q-Learning with Ordinal Rewards and Unreliable Tutor.” In In Proceedings ECML/PKDD-Workshop on Reinforcement Learning from Generalized Feedback:Beyond Numerical Rewards, Prague, 2013.

Busa-Fekete, Robert, B. Szörenyi, P. Weng, and Eyke Hüllermeier. “Preference-Based Evolutionary Direct Policy Search.” In In Proceedings ECML/PKDD-Workshop on Reinforcement Learning from Generalized Feedback:Beyond Numerical Rewards, Prague, 2013.

Cheng, W., and Eyke Hüllermeier. “A Nearest Neigbor Approach to Label Ranking Based on Generalized Labelwise Loss Minimization.” In In Proceedings M-PREF, 7th Multidisciplinary Workshop on Advances in Preference Handling Beijing, China, 2013.

Shaker, Ammar, and Eyke Hüllermeier. “Event History Analysis on Data Streams: An Application to Earthquake Occurence.” In In Proceedings RealStream 2013, 1st International Workshop on Real-World Challenges for Data Stream Mining, Prague, Czech Republic, edited by G. Krempl, I. Zliobaite, Y. Wang, and G. Forman, 38–41, 2013.

Senge, Robin, J.J. del Coz, and Eyke Hüllermeier. “On the Problem of Error Propagation in Classier Chains for Multi-Label Classification. Data Analysis, Machine Learning and Knowledge Discovery.” In In Proceedings of GFKL-2012, 36th Annual Conference of the German Classification Society, Studies in Classification, Data Analysis and Knowledge Organization, Hildesheim, Germany , edited by L. Schmidt-Thieme and M. Spiliopoulou. Springer, 2013.

Fober, T., G. Klebe, and Eyke Hüllermeier. “Local Clique Merging: An Extension of the Maximum Common Subgraph Measure with Applications in Structural Bioinformatics, Algorithms from and for Nature and Life.” In In Proceedings GFKL-2011, Conference of the German Classification Society, Frankfurt Germany, edited by B. Lausen, D. Van den Poel, and A. Ultsch, 279–86. Springer, 2013.

Fallah Tehrani, A., and Eyke Hüllermeier. “Ordinal Choquistic Regression .” In In Proceedings EUSFLAT-2013 8th International Conference on the European Society for Fuzzy Logic and Technology, Milano, Italy, edited by J. Montero, G. Pasi, and D. Ciucci. Atlantis Press, 2013.

Nasiri, N., T. Fober, Robin Senge, and Eyke Hüllermeier. “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 In Proceedings IFSA-2013 World Congress of the International Fuzzy Systems Association, Edmonton, Canada, 715–21, 2013.

Heider, D., Robin Senge, W. Cheng, and Eyke Hüllermeier. “Multilabel Classification for Exploiting Cross-Resistance Information in HIV-1 Drug Resistence Prediction.” Bioinformatics 29, no. 16 (2013): 1946–52.

Bösner, S., K. Bönisch, J. Haasenritter , P. Schlegel, Eyke Hüllermeier, and N. Donner-Banzhoff. “Chest Pain in Primary Care: Is the Localization of Pain Diagnostically Helpful in the Critical Evaluation of Patients? A Cross Sectional Study. .” BMC Family Practice 14, no. 1 (2013): 154–62.

Haasenritter, J., A. Viniol, A. Becker, S. Bösner, Eyke Hüllermeier, Robin Senge, and N. Donner-Banzhoff. “Diagnose Im Kontext - Eine Erweiterte Perspektive.” Zeitschrift Für Evidenz, Fortbildung Und Qualität Im Gesundheitswesen (ZEFQ) 107 (2013): 585–91.

Shaker, A., R. Senge, and Eyke Hüllermeier. “Evolving Fuzzy Pattern Trees for Binary Classification on Data Streams.” Information Sciences 220 (2013): 34–45.

Szarvas, G., Robert Busa-Fekete, and Eyke Hüllermeier. “Learning to Rank Lexical Substitutions.” In In Proceedings EMNLP-2013 Conference on Empirical Methods in Natural Language Processing, Seattle, USA, 2013.

Dembczynski, K., A. Jachnik, W. Kotlowski, W. Waegeman, and Eyke Hüllermeier. “Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization.” In In Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, edited by S. Dasgupta and D. McAllester, 1130–38, 2013.

Busa-Fekete, Robert, B. Szoreny, P. Weng, W. Cheng, and Eyke Hüllermeier. “Top-k Selection Based on Adaptive Sampling of Noisy Preferences.” In In Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, edited by S. Dasgupta and D. McAllester, 1094–1102, 2013.

Hüllermeier, Eyke, and W. Cheng. “Preference-Based CBR: General Ideas and Basic Principles.” In In Proceedings IJCAI-13, 23rd International Joint Conference on Artificial Intelligence, Beijing, China, edited by F. Rossi, 3012–16. AAAI Press, 2013.

Henzgen, Sascha, M. Strickert, and Eyke Hüllermeier. “Rule Chains for Visualizing Evolving Fuzzy Rule-Based Systems.” In In Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland, edited by R. Burduk, K. Jackowski, M. Kurzynski, M. Wozniak, and A. Zolnierek, 279–88. Springer, 2013.

Shaker, Ammar, and Eyke Hüllermeier. “Recovery Analysis for Adaptive Learning from Non-Stationary Data Streams.” In In Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland, edited by R. Burduk, K. Jackowski, M. Kurzynski, W. Wozniak, and A. Zolnierek, 289–98. Springer, 2013.

Leinweber, M., L. Baumgärtner, M. Mernberger, T. Fober, Eyke Hüllermeier, G. Klebe, and B. Freisleben. “GPU-Based Cloud Computing for Comparing the Structure of Protein Binding Sites.” In In Proceedings IEEE Conference on Digital Ecosystem Technologies-Complex Environment Engineering Campione D`Italia, Italy, 2012.