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443 Publications
2014 | Journal Article | LibreCat-ID: 10315
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.
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2014 | Journal Article | LibreCat-ID: 10316
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.
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2014 | Journal Article | LibreCat-ID: 10317
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.
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2014 | Journal Article | LibreCat-ID: 10318
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.
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2013 | Conference Paper | LibreCat-ID: 15752
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.
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2013 | Conference Paper | LibreCat-ID: 15753
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.
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2013 | Conference Paper | LibreCat-ID: 15755
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.
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2013 | Conference Paper | LibreCat-ID: 15756
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.
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2013 | Conference Paper | LibreCat-ID: 15757
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.
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2013 | Conference Paper | LibreCat-ID: 15758
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.
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2013 | Conference Paper | LibreCat-ID: 15759
Cheng, W., and Eyke Hüllermeier. “A Nearest Neigbor Approach to Label Ranking Based on Generalized Labelwise Loss Minimization.” In In Proceedings M-PREF`13, 7th Multidisciplinary Workshop on Advances in Preference Handling Beijing, China, 2013.
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2013 | Conference Paper | LibreCat-ID: 15760
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.
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2013 | Conference Paper | LibreCat-ID: 15761
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.
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2013 | Conference Paper | LibreCat-ID: 15763
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.
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2013 | Conference Paper | LibreCat-ID: 15112
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.
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2013 | Conference Paper | LibreCat-ID: 15113
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.
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2013 | Journal Article | LibreCat-ID: 16044
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.
LibreCat
2013 | Journal Article | LibreCat-ID: 16081
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.
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2013 | Journal Article | LibreCat-ID: 16086
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.
LibreCat
2013 | Journal Article | LibreCat-ID: 16123
Shaker, A., R. Senge, and Eyke Hüllermeier. “Evolving Fuzzy Pattern Trees for Binary Classification on Data Streams.” Information Sciences 220 (2013): 34–45.
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