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189 Publications


2014 | Conference Paper | LibreCat-ID: 353
Mohr, Felix, and Sven Walther. “Template-Based Generation of Semantic Services.” Proceedings of the 14th International Conference on Software Reuse (ICSR), 2014, pp. 188–203, doi:10.1007/978-3-319-14130-5_14.
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2014 | Conference Paper | LibreCat-ID: 428
Mohr, Felix. “Estimating Functional Reusability of Services.” Proceedings of the 12th International Conference on Service Oriented Computing (ICSOC), 2014, pp. 411–18.
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2014 | Conference Paper | LibreCat-ID: 10248
Busa-Fekete, Robert, and Eyke Hüllermeier. “A Survey of Preference-Based Online Learning with Bandit Algorithms.” Proceedings Int. Conf. on Algorithmic Learning Theory (ALT), Bled, Slovenia, 2014, pp. 18–39.
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2014 | Conference Paper | LibreCat-ID: 10250
Fallah Tehrani, A., et al. “The Choquet Kernel for Monotone Data.” Proceedings ESANN , Bruges, Belgium, 2014.
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2014 | Journal Article | LibreCat-ID: 10298
Calders, T., et al. “Guest Editors`introduction:Special Issue of the ECML/PKDD 2014 Journal Track.” Data Min. Knowledge Discovery, vol. 28, no. 5–6, 2014, pp. 1129–33.
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2014 | Journal Article | LibreCat-ID: 10318
Stock, M., et al. “Identification of Functionally Releated Enzymes by Learning to Rank Methods.” IEEE/ACM Trans. Comput. Biology Bioinform., vol. 11, no. 6, 2014, pp. 1157–69.
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2014 | Journal Article | LibreCat-ID: 10313
Calders, T., et al. “Guest Editors`introduction:Special Issue of the ECML/PKDD 2014 Journal Track.” Machine Learning, vol. 97, no. 1–2, 2014, pp. 1–3.
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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 | 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 | 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 | 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: 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: 10310
Strickert, M., et al. “Correlation-Based Embedding of Pairwise Score Data.” Neurocomputing, vol. 141, 2014, pp. 97–109.
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2014 | Conference Paper | LibreCat-ID: 457
Jungmann, Alexander, et al. “Applying Reinforcement Learning for Resolving Ambiguity in Service Composition.” Proceedings of the 7th International Conference on Service Oriented Computing and Applications (SOCA), 2014, pp. 105–12, doi:10.1109/SOCA.2014.48.
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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: 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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