Shaker, Ammar, and Eyke Hüllermeier. “Survival Analysis on Data Streams: Analyzing Temporal Events in Dynamically Changing Environments.” Applied Mathematics and Computer Science 24, no. 1 (2014): 199–212.

Hoffmann, F., Eyke Hüllermeier, and A. Kroll. “Ausgewählte Beiträge Des GMA-Fachausschusses 5.14.” Computational Intelligence Automatisierungstechnik 62, no. 10 (2014): 685–86.

Calders, T., F. Esposito, Eyke Hüllermeier, and R. Meo. “Guest Editors`introduction:Special Issue of the ECML/PKDD 2014 Journal Track.” Data Min. Knowledge Discovery 28, no. 5–6 (2014): 1129–33.

Henzgen, Sascha, M. Strickert, and Eyke Hüllermeier. “Visualization of Evolving Fuzzy Rule-Based Systems.” Evolving Systems 5, no. 3 (2014): 175–91.

Hüllermeier, Eyke. “Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization.” Int. J. Approx. Reasoning 55, no. 7 (2014): 1519–34.

Hüllermeier, Eyke. “Rejoinder on "Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization.” Int. J. Approx. Reasoning 55, no. 7 (2014): 1609–13.

Strickert, M., K. Bunte, F.- M. Schleif, and Eyke Hüllermeier. “Correlation-Based Embedding of Pairwise Score Data.” Neurocomputing 141 (2014): 97–109.

Senge, Robin, S. Bösner, K. Dembczynski, J. Haasenritter, O. Hirsch, N. Donner-Banzhoff, and Eyke Hüllermeier. “Reliable Classification: Learning Classifiers That Distinguish Aleatoric and Epistemic Uncertainty.” Information Sciences 255 (2014): 16–29.

Mernberger, M., M. Moog, S. Stork, S. Zauner, U.G. Maier, and Eyke Hüllermeier. “Protein Sub-Cellular Localization Prediction for Special Compartments via Optimized Time Series Distances.” J. Bioinformatics and Computational Biology 12, no. 1 (2014).

Calders, T., F. Esposito, Eyke Hüllermeier, and R. Meo. “Guest Editors`introduction:Special Issue of the ECML/PKDD 2014 Journal Track.” Machine Learning 97, no. 1–2 (2014): 1–3.

Busa-Fekete, Robert, B. Szörényi, P. Weng, W. Cheng, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning: Evolutionary Direct Policy Search Using a Preference-Based Racing Algorithm.” Machine Learning 97, no. 3 (2014): 327–51.

Montanés, E., Robin Senge, J. Barranquero, J.R. Quevedo, J.J. Del Coz, and Eyke Hüllermeier. “Dependent Binary Relevance Models for Multi-Label Classification.” Pattern Recognition 47, no. 3 (2014): 1494–1508.

Krempl, G., I. Zliobaite, D. Brzezinski, Eyke Hüllermeier, M. Last, V. Lemaire, T. Noack, et al. “Open Challenges for Data Stream Mining Research.” SIGKDD Explorations 16, no. 1 (2014): 1–10.

Krotzky, T., T. Fober, Eyke Hüllermeier, and G. Klebe. “Extended Graph-Based Models for Enhanced Similarity Search in Cavbase.” IEEE/ACM Trans. Comput. Biology Bioinform. 11, no. 5 (2014): 878–90.

Stock, M., T. Fober, Eyke Hüllermeier, S Glinca, G. Klebe, T. Pahikkala, A. Airola, B. De Baets, and W. Wageman. “Identification of Functionally Releated Enzymes by Learning to Rank Methods.” IEEE/ACM Trans. Comput. Biology Bioinform. 11, no. 6 (2014): 1157–69.

Mohr, Felix, and Hans Kleine Büning. “Semi-Automated Software Composition Through Generated Components.”https://doi.org/10.1145/2539150.2539235__In Proceedings of the 15th International Conference on Information Integration and Web-Based Applications &; Services (IiWAS), 676–80, 2013.https://doi.org/10.1145/2539150.2539235 .

Mohr, Felix, Theodor Lettmann, and Hans Kleine Büning. “Reducing Nondeterminism in Automated Service Composition.”https://doi.org/10.1109/SOCA.2013.25__In Proceedings of the 6th International Conference on Service Oriented Computing and Applications (SOCA), 154–61, 2013.https://doi.org/10.1109/SOCA.2013.25 .

Cheng, W., S. Henzgen, and Eyke Hüllermeier. “Labelwise versus Pairwise Decomposition in Label Ranking.” In In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Bamberg, Germany, 129–36, 2013.

Senge, Robin, J. del Coz, and Eyke Hüllermeier. “Rectifying Classifier Chains for Multi-Label Classification, Bamberg, Germany.” In In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Bamberg, Germany, 151–58, 2013.

Busa-Fekete, Robert, T. Fober, and Eyke Hüllermeier. “Preference-Based Evolutionary Optimization Using Generalized Racing Algorithms.” In In Proceedings 23th Workshop Computational Intelligence, Dortmund Germany, edited by F. Hoffmann and Eyke Hüllermeier, 237–46. KIT Scientific Publishing, 2013.

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.

Hüllermeier, Eyke, and A. Fallah Tehrani. “Efficient Learning of Classifiers Based on the 2-Additive Choquet Integral.” In Computational Intelligence in Intelligent Data Analysis, edited by C. Moewes and A. Nürnberger, 17–30. Studies in Computational Intelligence. Springer, 2012.

Bräuning, M., and Eyke Hüllermeier. “Learning Conditional Lexicographic Preference Trees.” In In Workshops on Preference Learning at ECAI, European Conference on Artiticial Intelligence, Montpellier, France, 2012.

Hüllermeier, Eyke, and A. Fallah Tehrani. “On the VC Dimension of the Choquet Integral.” In In Proceedings IPMU-2012 14th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Catania, Italy, 2012.

Fallah Tehrani, A., W. Cheng, K. Dembczynski, and Eyke Hüllermeier. “Learning  Monotone Nonlinear Models Using the Choquet Integral.” Machine Learning 89, no. 1 (2012): 183–211.

Bustince, H., M. Pagola, R. Mesiar, Eyke Hüllermeier, and F. Herrera. “Grouping, Overlap and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons.” IEEE Transactions on Fuzzy Systems 20, no. 3 (2012): 405–15.

Fürnkranz, J., Eyke Hüllermeier, W. Cheng, and S.H. Park. “Preference-Based Reinforcement Learning: A Formal Framework and a Policy Iteration Algorithm.” Machine Learning 89, no. 1 (2012): 123–56.

Dembczynski, K., W. Waegeman, W. Cheng, and Eyke Hüllermeier. “On Label Dependence and Loss  Minimization in Multi-Label Classification.” Machine Learning 88, no. 1–2 (2012): 5–45.

Shaker, Ammar, and Eyke Hüllermeier. “IBL Streams: A System for Instance-Based Classification and Regression on Data Streams.” Evolving Systems 3, no. 4 (2012): 235–49.

Dolorez Ruiz, M., and Eyke Hüllermeier. “A Formal and Empirical Analysis of the Fuzzy Gamma Rank Correlation Coefficient.” Information Sciences 206 (2012): 1–17.

Fallah Tehrani, A., W. Cheng, and Eyke Hüllermeier. “Preference Learning Using the Choquet Integral: The Case of Multipartite Ranking.” IEEE Transactions on Fuzzy Systems 20, no. 6 (2012): 1102–13.

Fober, T., M. Mernberger, G. Klebe, and Eyke Hüllermeier. “Fingerprint Kernels for Protein Structure Comparison.” Molecular Informatics 31, no. 6–7 (2012): 443–52.

Hüllermeier, Eyke, M. Rifqi, Sascha Henzgen, and Robin Senge. “Comparing Fuzzy Partitions: A Generalization of the Rand Index and Related Measures.” IEEE Transactions on Fuzzy Systems 20, no. 3 (2012): 546–56.

Senge, Robin, T. Fober, N. Nasiri, and Eyke Hüllermeier. “Fuzzy Pattern Trees: Ein Alternativer Ansatz Zur Fuzzy-Modellierung.” At-Atomatisierungstechnik 60, no. 10 (2012): 622–29.

Cheng, W., Eyke Hüllermeier, W. Waegeman, and V. Welker. “Label Ranking with Partial Abstention Based on Thresholded Probalistic Models.” In In Proceedings NIPS-2012, 26th Annual Conference on Neural Information Processing Systems, Lake Tahoe, Nevada, USA, 2012.

Cheng, W., and Eyke Hüllermeier. “Probability Estimation for Mulit-Class Classification Based on Label Ranking.” In Proceedings ECML/PKDD-2012, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Bristol, UK, 2012.

Dembczynski, K., W. Kotlowski, and Eyke Hüllermeier. “Consistent Multilabel Ranking through Univariate Loss Minimization.” In In Proceedings ICML-2012,  International Conference on Machine Learning, Edinburgh, Scotland, edited by J. Langford and J. Pineau, 2012.

Dembczynski, K., W. Waegeman, and Eyke Hüllermeier. “An Analysis of Chaining in Multi-Label Classification.” In In Proceedings ECAI-2012, 20th European Conference on Artificial Inteligence, Montpellier, France , 294–99. IOS Press, 2012.

Hüllermeier, Eyke. “Fuzzy Rules in Data Mining: From Fuzzy Associations to Gradual Dependencies.” In Combining Experimentation and Theory, edited by E. Trillas, P.P. Bonissone, L. Magdalena, and J. Kacprzyk, 271:123–35. Studies in Fuzziness and Soft Computing. Springer, 2012.

Dembczynski, K., W. Waegeman, and Eyke Hüllermeier. “Joint Mode Estimation in Multi-Label Classification by Chaining.” In In Proceedings ECML Workshop on Collective Inference and Learning on Structured Data, Athens, Greece, 2011.

Mernberger, M., D. Moog, S. Stork, S. Zauner, U. Maier, and Eyke Hüllermeier. “Prediction of Protein Localization for Specialized Compartments Using Time Series Kernels.” In In Proceedings GCB-2011 German Conference on Bioinformatics Munich, Germany, 2011.

Nasiri, M., Eyke Hüllermeier, Robin Senge, and E. Lughofer. “Comparing Methods for Knowledge-Driven and Data-Driven Fuzzy Modeling: A Case Study in Textile Industry.” In In Proceedings IFSA-2011 World Congress of the International Fuzzy Systems Association, Surabaya and Bali Island, Indonesia, RW-103-1-6, 2011.

Lughofer, E., and Eyke Hüllermeier. “On-Line Redundancy Deletion in Evolving Fuzzy Regression Models Using a Fuzzy Inclusion Measure.” In In Proceedings EUSFLAT-2011 7th International Conference on the European Society for Fuzzy Logic and Technology, Aix-Les-Bains, France, edited by S. Galichet, J. Montero, and G. Mauris, 380–87, 2011.

Fallah Tehrani, A., W. Cheng, and Eyke Hüllermeier. “Choquistic Regression: Generalizing Logistic Regression Using the Choquet Integral.” In In Proceedings EUSFLAT-2011 7th International Conference on the European Society for Fuzzy Logic and Technology, Aix-Les-Bains, France, 868–75, 2011.

Hirsch, O., S. Bösner, Eyke Hüllermeier, R. Senge, K. Dembczynski, and N. Donner-Banzhoff. “Multivariate Modeling to Identify Patterns in Clinical Data: The Example of Chest Pain.” BMC Medical Research Methodology 11, no. 155 (2011).

Domshlak, C., Eyke Hüllermeier, S. Kaci, and H. Prade. “Preferences in AL: An Overview.” Artificial Intelligence 175, no. 7–8 (2011): 1037–52.

Hüllermeier, Eyke. “Fuzzy Machine Learning and Data Mining.” WIREs Data Mining and Knowledge Discovery 1, no. 4 (2011): 269–83.

Mernberger, M., G. Klebe, and Eyke Hüllermeier. “SEGA: Semi-Global Graph Alignment for Structure-Based Protein Comparison.” IEEE/ACM Transactions of Computational Biology and Bioinformatics 8, no. 5 (2011): 1330–43.

Fober, T., S. Glinca, G. Klebe, and Eyke Hüllermeier. “Superposition and Alignment of Labeled Point Clouds.” IEEE/ACM Transactions on Computational Biology and Bioinformatics 8, no. 6 (2011): 1653–66.

Hüllermeier, Eyke. “Fuzzy Sets in Machine Learning and Data Mining.” Applied Soft Computing Journal, 2011, 1493–1505.

Senge, Robin, and Eyke Hüllermeier. “Top-down Induction of Fuzzy Pattern Trees.” IEEE Transactions on Fuzzy Systems 19, no. 2 (2011): 241–52.

Dembczynski, K., W. Waegeman, W. Cheng, and Eyke Hüllermeier. “An Exact Algorithm for F-Measure Maximization.” In In Proceedings NIPS-2011, 25th Annual Conference on Neural Information Processing Systems, Granada, Spain, 2011.

Fürnkranz, J., and Eyke Hüllermeier. “Learning from Label Preferences.” In In Proceedings DS-2011, 14th International  Conference on Discovery Science, Number 6926 in LNAI, edited by T. Elomaa, J. Hollmen, and H. Mannila, 2–17. Springer, 2011.

Fallah Tehrani, A., W. Cheng, K. Dembczynski, and Eyke Hüllermeier. “Learning  Monotone Nonlinear Models Using the Choquet Integral.” In In Proceedings ECML/PKDD-2011, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Athens, Greece, 2011.

Hüllermeier, Eyke, and P. Schlegel. “Preference-Based CBR: First Steps toward a Methodological Framework.” In In Proceedings ICCBR-2011, 19th International Conference on Case-Based Reasoning, Number 6880 in LNAI, edited by A. Ram and N. Wiratunga, 77–91. Springer, 2011.

Kotlowski, W., K. Dembczynski, and Eyke Hüllermeier. “Bipartite Ranking through Minimization of Univariate Loss.” In In Proceedings ICML-2011, 28th International Conference on Machine Learning, Washington, USA, 2011.

Hüllermeier, Eyke, and J. Hühn. “An Analysis of the FURIA Algorithm for Fuzzy Rule Induction.” In Advances in Machine Learning I: Dedicated to the Memory of Professor Ryszard S.Michalski, edited by J. Koronacki, Z.W. Ras, S.T. Wierzchon, and J. Kacprzyk, 262:321–44. Studies in Computational Intelligence. Springer, 2010.

Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning: An Introduction.” In Preference Learning, edited by J. Fürnkranz and Eyke Hüllermeier, 1–18. Springer, 2010.

Fober, T., M. Mernberger, G. Klebe, and Eyke Hüllermeier. “Efficient Similarity Retrieval for Protein Binding Sites Based on Histogram Comparison.” In In Proceedings GCB-2010 German Conference on Bioinformatics Braunschweig, Germany, 51–60, 2010.

Dembczynski, K., W. Waegeman, W. Cheng, and Eyke Hüllermeier. “On Label Dependence in Multi-Label Classification.” In In Proceedings MLD-2010, 2nd International Workshop on Learning from Multi-Label Data, Haifa, Israel, 2010.

Fober, T., and Eyke Hüllermeier. “Similarity Measures for Protein Structures Based on Fuzzy Histogram Comparison.” In In Proceedings WCCI-2010, World Congress on Computational Intelligence, Barcelona, Spain, 2010.

Senge, Robin, and Eyke Hüllermeier. “Pattern Trees for Regression and Fuzzy Systems Modeling.” In In Proceedings WCCI-2010, World Congress on Computational Intelligence, Barcelona, Spain, 2010.

Pfeffer, P., T. Fober, Eyke Hüllermeier, and G. Klebe. “GARLig: A Fully Automated Tool for Subset Selection of Large Fragment Spaces via a Self-Adaptive Genetic Algorithm.” Journal of Chemical Information and Modeling 50, no. 9 (2010): 1644–59.

Hüllermeier, Eyke, and S. Vanderlooy. “Combining Predictions in Pairwise Classification: An Optimal Adaptive Voting Strategy and Its Relation to Weighted Voting.” Pattern Recognition 43, no. 1 (2010): 128–42.

Hüllermeier, Eyke, and J. Fürnkranz. “On Predictive Accuracy and Risk Minimization in Pairwise Label Ranking.” Journal of Computer and System Sciences 76, no. 1 (2010): 49–62.

Dembczynski, K., W. Cheng, and Eyke Hüllermeier. “Bayes Optimal Multilabel Classification via Probalistic Classifier Chains.” In In Proceedings ICML-2010, 27th International Conference on Machine Learning, Haifa, Israel, edited by J. Fürnkranz and T. Joachims, 279–86, 2010.

Cheng, W., K. Dembczynski, and Eyke Hüllermeier. “Label Ranking Based on the Plackett-Luce Model.” In In Proceedings ICML-2010, 27th International Conference on Machine Learning, Haifa, Israel, edited by J. Fürnkranz and T. Joachims, 215–22, 2010.

Cheng, W., K. Dembczynski, and Eyke Hüllermeier. “Graded Multi-Label Classification: The Ordinal Case.” In In Proceedings ICML-2010, 27th International Conference on Machine Learning, Haifa, Israel, edited by J. Fürnkranz and T. Joachims, 2010.

Dembczynski, K., W. Waegeman, W. Cheng, and Eyke Hüllermeier. “Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss.” In In Proceedings ECML/PKDD-2010, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ,Bareclona, Spain, 2010.

Cheng, W., M. Rademaker, B. De Beats, and Eyke Hüllermeier. “Predicting Partial Orders: Ranking with Abstention.” In In Proceedings ECML/PKDD-2010, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ,Bareclona, Spain, 2010.

Hüllermeier, Eyke. “Uncertainty in Clustering and Classification .” In In Proceedings SUM 2010, International Conference on Scalable Uncertainty Management , 6379:16–19. Springer, 2010.

Cheng, W., and Eyke Hüllermeier. “A Simple Instance-Based Approach to Multilabel Classification Using the Mallows Model.” In In Proceedings MLD-2009 1st  International Workshop on Learning from Multi-Label Data, Bled, Slovenia, 28–38, 2009.

Senge, Robin, and Eyke Hüllermeier. “Learning Pattern Tree Classifiers Using a Co-Evolutionary Algorithm.” In In Proceedings 19th Workshop Computational Intelligence, Dortmund Germany, edited by F. Hoffmann and Eyke Hüllermeier, 22–33. KIT Scientific Publishing, 2009.

Fober, T., M. Mernberger, R. Moritz, and Eyke Hüllermeier. “Graph-Kernels for the Comparative Analysis of Protein Active Sites.” In In Proceedings GCB-2009 German Conference on Bioinformatics Halle (Saale), Germany, edited by I. Grosse, S. Neumann, S. Posch, F. Schreiber, and P.. Stadler, 21–31, 2009.

Senge, Robin, and Eyke Hüllermeier. “Learning Pattern Tree Classifiers Using a Co-Evolutionary Algorithm.” In In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Darmstadt, Germany, 105–10, 2009.

Fober, T., M. Mernberger, Vitaly Melnikov, R. Moritz, and Eyke Hüllermeier. “Extension and Empirical Comparison of Graph-Kernels for the Analysis of Protein Active Sites.” In In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Darmstadt, Germany, 30–36, 2009.

Fober, T., G. Klebe, and Eyke Hüllermeier. “Efficient Construction of Multiple Geometrical Alignments for the Comparison of Protein Binding Sites.” In In Proceedings ISDA-2009, 9th International Conference on Intelligent Systems Design and Applications, Pisa, Italy, 1251–56, 2009.

Boukhris, I., Z. Elouedi, T. Fober, M. Mernberger, and Eyke Hüllermeier. “Similarity Analysis of Protein Binding Sites: A Generalization of the Maximum Common Subgraph Measure Based on Quasi-Clique Detection.” In In Proceedings IDA-2009, 9th International Symposium on Intelligent Data Analysis, Pisa / Italy, 1245–50, 2009.

Fober, T., and Eyke Hüllermeier. “Fuzzy Modeling of Labeled Point Cloud Superposition  for the Comparison of Protein Binding Sites.” In In Proceedings IFSA / EUSFLAT-2009 World Congress of  the Fuzzy Systems Association, Lissabon, Portugal, 1299–1304, 2009.

Hüllermeier, Eyke, and M. Rifqi. “A Fuzzy Variant of the Rand Index for Comparing Clustering Structures.” In In Proceedings IFSA / EUSFLAT-2009 World Congress of  the Fuzzy Systems Association, Lissabon, Portugal, 1294–98, 2009.

Weskamp, N., Eyke Hüllermeier, and G. Klebe. “Merging Chemical and Biological Space: Structural Mapping of Enzyme Binding Pocket Space.” Proteins 76, no. 2 (2009): 317–30.