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449 Publications
2014 | Journal Article | LibreCat-ID: 16082
R. Senge et al., “Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty,” Information Sciences, vol. 255, pp. 16–29, 2014.
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2014 | Journal Article | LibreCat-ID: 16083
N. Donner-Banzhoff, J. Haasenritter, E. Hüllermeier, A. Viniol, S. Bösner, and A. Becker, “The comprehensive diagnostic study is suggested as a design to model the diagnostic process,” Journal of Clinical Epidemiology, vol. 2, no. 67, pp. 124–132, 2014.
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2014 | Conference Paper | LibreCat-ID: 10247
R. Busa-Fekete, B. Szörényi, and E. Hüllermeier, “PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences,” in Proceedings AAAI 2014, Quebec, Canada, 2014, pp. 1701–1707.
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2014 | Conference Paper | LibreCat-ID: 10248
R. Busa-Fekete and E. Hüllermeier, “A Survey of Preference-Based Online Learning with Bandit Algorithms,” in Proceedings Int. Conf. on Algorithmic Learning Theory (ALT), Bled, Slovenia, 2014, pp. 18–39.
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2014 | Conference Paper | LibreCat-ID: 10249
S. Henzgen and E. Hüllermeier, “Mining Rank Data,” in Proceedings Discovery Science, Bled,Slovenia , 2014, pp. 123–134.
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2014 | Conference Paper | LibreCat-ID: 10250
A. Fallah Tehrani, M. Strickert, and E. Hüllermeier, “The Choquet kernel for monotone data,” in Proceedings ESANN , Bruges, Belgium, 2014.
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2014 | Conference Paper | LibreCat-ID: 10251
A. Abdel-Aziz, M. Strickert, and E. Hüllermeier, “Learning Solution Similarity in Preference-Based CBR,” in Proceedings Int. Conf. Case-Based Reasoning (ICCBR), Cork, Ireland, 2014, pp. 17–31.
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2014 | Conference Paper | LibreCat-ID: 10253
D. Schäfer and E. Hüllermeier, “Dyad Ranking Using A Bilinear Plackett-Luce Model,” in Proceedings Lernen-Wissensentdeckung-Adaptivität (LWA), Aachen, Germany, 2014, pp. 32–33.
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2014 | Conference Paper | LibreCat-ID: 10254
T. Calders, F. Esposito, E. Hüllermeier, and R. Meo, “Machine Learning and Knowledge Discovery in Databases-European Conf. ECML/PKDD, Nancy, France,” in Proceedings, Parts I-III. Lecture Notes in Computer Science, 2014, pp. 8724–8726.
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2014 | Conference Paper | LibreCat-ID: 10295
J. Fürnkranz, E. Hüllermeier, C. Rudin, R. Slowinski, and S. Sanner, “Preference Learning (Dagstuhl Seminar 14101) Dagstuhl Reports,” 2014, vol. 4, no. 3, pp. 1–27.
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2014 | Journal Article | LibreCat-ID: 10296
A. Shaker and E. Hüllermeier, “Survival analysis on data streams: Analyzing temporal events in dynamically changing environments,” Applied Mathematics and Computer Science, vol. 24, no. 1, pp. 199–212, 2014.
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2014 | Journal Article | LibreCat-ID: 10297
F. Hoffmann, E. Hüllermeier, and A. Kroll, “Ausgewählte Beiträge des GMA-Fachausschusses 5.14,” Computational Intelligence Automatisierungstechnik, vol. 62, no. 10, pp. 685–686, 2014.
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2014 | Journal Article | LibreCat-ID: 10298
T. Calders, F. Esposito, E. Hüllermeier, and R. Meo, “Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track,” Data Min. Knowledge Discovery, vol. 28, no. 5–6, pp. 1129–1133, 2014.
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2014 | Journal Article | LibreCat-ID: 10299
S. Henzgen, M. Strickert, and E. Hüllermeier, “Visualization of evolving fuzzy rule-based systems,” Evolving Systems, vol. 5, no. 3, pp. 175–191, 2014.
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2014 | Journal Article | LibreCat-ID: 10308
E. Hüllermeier, “Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization,” Int. J. Approx. Reasoning, vol. 55, no. 7, pp. 1519–1534, 2014.
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2014 | Journal Article | LibreCat-ID: 10309
E. Hüllermeier, “Rejoinder on "Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization,” Int. J. Approx. Reasoning, vol. 55, no. 7, pp. 1609–1613, 2014.
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2014 | Journal Article | LibreCat-ID: 10310
M. Strickert, K. Bunte, F.-M. Schleif, and E. Hüllermeier, “Correlation-based embedding of pairwise score data,” Neurocomputing, vol. 141, pp. 97–109, 2014.
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2014 | Journal Article | LibreCat-ID: 10311
R. Senge et al., “Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty,” Information Sciences, vol. 255, pp. 16–29, 2014.
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2014 | Journal Article | LibreCat-ID: 10312
M. Mernberger, M. Moog, S. Stork, S. Zauner, U. G. Maier, and E. Hüllermeier, “Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances,” J. Bioinformatics and Computational Biology, vol. 12, no. 1, 2014.
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2014 | Journal Article | LibreCat-ID: 10313
T. Calders, F. Esposito, E. Hüllermeier, and R. Meo, “Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track,” Machine Learning, vol. 97, no. 1–2, pp. 1–3, 2014.
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2014 | Journal Article | LibreCat-ID: 10314
R. Busa-Fekete, B. Szörényi, P. Weng, W. Cheng, and E. Hüllermeier, “Preference-Based Reinforcement Learning: evolutionary direct policy search using a preference-based racing algorithm,” Machine Learning, vol. 97, no. 3, pp. 327–351, 2014.
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2014 | Journal Article | LibreCat-ID: 10315
E. Montanés, R. Senge, J. Barranquero, J. R. Quevedo, J. J. Del Coz, and E. Hüllermeier, “Dependent binary relevance models for multi-label classification,” Pattern Recognition, vol. 47, no. 3, pp. 1494–1508, 2014.
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2014 | Journal Article | LibreCat-ID: 10316
G. Krempl et al., “Open challenges for data stream mining research,” SIGKDD Explorations, vol. 16, no. 1, pp. 1–10, 2014.
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2014 | Journal Article | LibreCat-ID: 10317
T. Krotzky, T. Fober, E. Hüllermeier, and G. Klebe, “Extended Graph-Based Models for Enhanced Similarity Search in Cavbase,” IEEE/ACM Trans. Comput. Biology Bioinform., vol. 11, no. 5, pp. 878–890, 2014.
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2014 | Journal Article | LibreCat-ID: 10318
M. Stock et al., “Identification of Functionally Releated Enzymes by Learning to Rank Methods,” IEEE/ACM Trans. Comput. Biology Bioinform., vol. 11, no. 6, pp. 1157–1169, 2014.
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2013 | Conference Paper | LibreCat-ID: 485
F. Mohr and H. Kleine Büning, “Semi-Automated Software Composition Through Generated Components,” in Proceedings of the 15th International Conference on Information Integration and Web-based Applications & Services (iiWAS), 2013, pp. 676–680.
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2013 | Conference Paper | LibreCat-ID: 495
F. Mohr, T. Lettmann, and H. Kleine Büning, “Reducing Nondeterminism in Automated Service Composition,” in Proceedings of the 6th International Conference on Service Oriented Computing and Applications (SOCA), 2013, pp. 154–161.
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2013 | Conference Paper | LibreCat-ID: 15752
W. Cheng, S. Henzgen, and E. Hüllermeier, “Labelwise versus pairwise decomposition in label ranking,” in In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Bamberg, Germany, 2013, pp. 129–136.
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2013 | Conference Paper | LibreCat-ID: 15753
R. Senge, J. del Coz, and E. Hüllermeier, “Rectifying classifier chains for multi-label classification, Bamberg, Germany,” in In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Bamberg, Germany, 2013, pp. 151–158.
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2013 | Conference Paper | LibreCat-ID: 15755
R. Busa-Fekete, T. Fober, and E. Hüllermeier, “Preference-based evolutionary optimization using generalized racing algorithms,” in in Proceedings 23th Workshop Computational Intelligence, Dortmund Germany, 2013, pp. 237–246.
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2013 | Conference Paper | LibreCat-ID: 15756
S. Henzgen and E. Hüllermeier, “Weighted rank correlation measures based on fuzzy order relations,” in in Proceedings 23th Workshop Computational Intelligence, Dortmund Germany, 2013, pp. 227–236.
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2013 | Conference Paper | LibreCat-ID: 15757
P. Weng, R. Busa-Fekete, and E. 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
R. Busa-Fekete, B. Szörenyi, P. Weng, and E. 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
W. Cheng and E. 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
A. Shaker and E. 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, 2013, pp. 38–41.
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2013 | Conference Paper | LibreCat-ID: 15761
R. Senge, J. J. del Coz, and E. 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 , 2013.
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2013 | Conference Paper | LibreCat-ID: 15763
T. Fober, G. Klebe, and E. 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, 2013, pp. 279–286.
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2013 | Conference Paper | LibreCat-ID: 15112
A. Fallah Tehrani and E. Hüllermeier, “Ordinal Choquistic regression ,” in in Proceedings EUSFLAT-2013 8th International Conference on the European Society for Fuzzy Logic and Technology, Milano, Italy, 2013.
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2013 | Conference Paper | LibreCat-ID: 15113
N. Nasiri, T. Fober, R. Senge, and E. 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, 2013, pp. 715–721.
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2013 | Journal Article | LibreCat-ID: 16044
D. Heider, R. Senge, W. Cheng, and E. Hüllermeier, “Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistence prediction,” Bioinformatics, vol. 29, no. 16, pp. 1946–1952, 2013.
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2013 | Journal Article | LibreCat-ID: 16081
S. Bösner, K. Bönisch, J. Haasenritter , P. Schlegel, E. 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, vol. 14, no. 1, pp. 154–162, 2013.
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2013 | Journal Article | LibreCat-ID: 16086
J. Haasenritter et al., “Diagnose im Kontext - eine erweiterte Perspektive,” Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen (ZEFQ), vol. 107, pp. 585–591, 2013.
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2013 | Journal Article | LibreCat-ID: 16123
A. Shaker, R. Senge, and E. Hüllermeier, “Evolving fuzzy pattern trees for binary classification on data streams,” Information Sciences, vol. 220, pp. 34–45, 2013.
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2013 | Conference Paper | LibreCat-ID: 13115
G. Szarvas, R. Busa-Fekete, and E. Hüllermeier, “Learning to rank lexical substitutions,” in In Proceedings EMNLP-2013 Conference on Empirical Methods in Natural Language Processing, Seattle, USA, 2013.
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2013 | Conference Paper | LibreCat-ID: 13116
K. Dembczynski, A. Jachnik, W. Kotlowski, W. Waegeman, and E. 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, 2013, pp. 1130–1138.
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2013 | Conference Paper | LibreCat-ID: 13117
R. Busa-Fekete, B. Szoreny, P. Weng, W. Cheng, and E. Hüllermeier, “Top-k selection based on adaptive sampling of noisy preferences,” in in Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, 2013, pp. 1094–1102.
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2013 | Conference Paper | LibreCat-ID: 13118
E. Hüllermeier 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, 2013, pp. 3012–3016.
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2013 | Conference Paper | LibreCat-ID: 13119
S. Henzgen, M. Strickert, and E. Hüllermeier, “Rule chains for visualizing evolving fuzzy rule-based systems,” in in Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland, 2013, pp. 279–288.
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2013 | Conference Paper | LibreCat-ID: 13190
A. Shaker and E. 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, 2013, pp. 289–298.
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2012 | Conference Paper | LibreCat-ID: 15299
M. Leinweber et al., “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.
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