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418 Publications


2014 | Conference Paper | LibreCat-ID: 10249
Henzgen, Sascha, and Eyke Hüllermeier. “Mining Rank Data.” Proceedings Discovery Science, Bled,Slovenia , 2014, pp. 123–34.
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2014 | Conference Paper | LibreCat-ID: 10251
Abdel-Aziz, A., et al. “Learning Solution Similarity in Preference-Based CBR.” Proceedings Int. Conf. Case-Based Reasoning (ICCBR), Cork, Ireland, 2014, pp. 17–31.
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2014 | Journal Article | LibreCat-ID: 10299
Henzgen, Sascha, et al. “Visualization of Evolving Fuzzy Rule-Based Systems.” Evolving Systems, vol. 5, no. 3, 2014, pp. 175–91.
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2014 | Journal Article | LibreCat-ID: 10314
Busa-Fekete, Robert, et al. “Preference-Based Reinforcement Learning: Evolutionary Direct Policy Search Using a Preference-Based Racing Algorithm.” Machine Learning, vol. 97, no. 3, 2014, pp. 327–51.
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2014 | Journal Article | LibreCat-ID: 16064
Hüllermeier, Eyke. “Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization.” International Journal of Approximate Reasoning, vol. 55, no. 7, 2014, pp. 1519–34.
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2014 | Journal Article | LibreCat-ID: 16069
Henzgen, Sascha, et al. “Visualization of Evolving Fuzzy-Rule-Based Systems.” Evolving Systems, vol. 5, 2014, pp. 175–91.
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2014 | Journal Article | LibreCat-ID: 16083
Donner-Banzhoff, N., et al. “The Comprehensive Diagnostic Study Is Suggested as a Design to Model the Diagnostic Process.” Journal of Clinical Epidemiology, vol. 2, no. 67, 2014, pp. 124–32.
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2014 | Conference Paper | LibreCat-ID: 10295
Fürnkranz, J., et al. Preference Learning (Dagstuhl Seminar 14101) Dagstuhl Reports. Vol. 4, no. 3, 2014, pp. 1–27.
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2014 | Journal Article | LibreCat-ID: 10308
Hüllermeier, Eyke. “Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization.” Int. J. Approx. Reasoning, vol. 55, no. 7, 2014, pp. 1519–34.
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2014 | Journal Article | LibreCat-ID: 10310
Strickert, M., et al. “Correlation-Based Embedding of Pairwise Score Data.” Neurocomputing, vol. 141, 2014, pp. 97–109.
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2014 | Journal Article | LibreCat-ID: 10315
Montanés, E., et al. “Dependent Binary Relevance Models for Multi-Label Classification.” Pattern Recognition, vol. 47, no. 3, 2014, pp. 1494–508.
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2014 | Journal Article | LibreCat-ID: 16046
Agarwal, M., et al. “Preference-Based Learning of Ideal Solutions in TOPSIS-like Decision Models.” Journal of Multi-Criteria Decision Analysis, vol. 22, no. 3–4, 2014.
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2014 | Journal Article | LibreCat-ID: 16060
Krotzky, T., et al. “Extended Graph-Based Models for Enhanced Similarity Search in Cabase.” IEEE/ACM Transactions of Computational Biology and Bioinformatics, vol. 11, no. 5, 2014, pp. 878–90.
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2014 | Journal Article | LibreCat-ID: 16077
Busa-Fekete, Robert, et al. “Preference-Based Reinforcement Learning: Evolutionary Direct Policy Search Using a Preference-Based Racing Algorithm.” Machine Learning, vol. 97, no. 3, 2014, pp. 327–51.
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2014 | Journal Article | LibreCat-ID: 10296
Shaker, Ammar, and Eyke Hüllermeier. “Survival Analysis on Data Streams: Analyzing Temporal Events in Dynamically Changing Environments.” Applied Mathematics and Computer Science, vol. 24, no. 1, 2014, pp. 199–212.
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2014 | Journal Article | LibreCat-ID: 10309
Hüllermeier, Eyke. “Rejoinder on "Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization.” Int. J. Approx. Reasoning, vol. 55, no. 7, 2014, pp. 1609–13.
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2014 | Journal Article | LibreCat-ID: 10311
Senge, Robin, et al. “Reliable Classification: Learning Classifiers That Distinguish Aleatoric and Epistemic Uncertainty.” Information Sciences, vol. 255, 2014, pp. 16–29.
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2014 | Journal Article | LibreCat-ID: 10316
Krempl, G., et al. “Open Challenges for Data Stream Mining Research.” SIGKDD Explorations, vol. 16, no. 1, 2014, pp. 1–10.
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2014 | Conference Paper | LibreCat-ID: 10253
Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using A Bilinear Plackett-Luce Model.” Proceedings Lernen-Wissensentdeckung-Adaptivität (LWA), Aachen, Germany, 2014, pp. 32–33.
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2014 | Journal Article | LibreCat-ID: 16078
Krempl, G., et al. “Open Challenges for Data Stream Mining Research.” SIGKDD Explorations, vol. 16, no. 1, 2014, pp. 1–10.
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