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189 Publications


2014 | Conference Paper | LibreCat-ID: 353
Mohr, F., & Walther, S. (2014). Template-based Generation of Semantic Services. In Proceedings of the 14th International Conference on Software Reuse (ICSR) (pp. 188–203). https://doi.org/10.1007/978-3-319-14130-5_14
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2014 | Conference Paper | LibreCat-ID: 428
Mohr, F. (2014). Estimating Functional Reusability of Services. In Proceedings of the 12th International Conference on Service Oriented Computing (ICSOC) (pp. 411–418).
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2014 | Conference Paper | LibreCat-ID: 10248
Busa-Fekete, R., & Hüllermeier, E. (2014). A Survey of Preference-Based Online Learning with Bandit Algorithms. In Proceedings Int. Conf. on Algorithmic Learning Theory (ALT), Bled, Slovenia (pp. 18–39).
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2014 | Conference Paper | LibreCat-ID: 10250
Fallah Tehrani, A., Strickert, M., & Hüllermeier, E. (2014). The Choquet kernel for monotone data. In Proceedings ESANN , Bruges, Belgium.
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2014 | Journal Article | LibreCat-ID: 10298
Calders, T., Esposito, F., Hüllermeier, E., & Meo, R. (2014). Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track. Data Min. Knowledge Discovery, 28(5–6), 1129–1133.
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2014 | Journal Article | LibreCat-ID: 10318
Stock, M., Fober, T., Hüllermeier, E., Glinca, S., Klebe, G., Pahikkala, T., … Wageman, W. (2014). Identification of Functionally Releated Enzymes by Learning to Rank Methods. IEEE/ACM Trans. Comput. Biology Bioinform., 11(6), 1157–1169.
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2014 | Journal Article | LibreCat-ID: 10313
Calders, T., Esposito, F., Hüllermeier, E., & Meo, R. (2014). Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track. Machine Learning, 97(1–2), 1–3.
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2014 | Conference Paper | LibreCat-ID: 10251
Abdel-Aziz, A., Strickert, M., & Hüllermeier, E. (2014). Learning Solution Similarity in Preference-Based CBR. In Proceedings Int. Conf. Case-Based Reasoning (ICCBR), Cork, Ireland (pp. 17–31).
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2014 | Conference Paper | LibreCat-ID: 10249
Henzgen, S., & Hüllermeier, E. (2014). Mining Rank Data. In Proceedings Discovery Science, Bled,Slovenia (pp. 123–134).
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2014 | Journal Article | LibreCat-ID: 10299
Henzgen, S., Strickert, M., & Hüllermeier, E. (2014). Visualization of evolving fuzzy rule-based systems. Evolving Systems, 5(3), 175–191.
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2014 | Journal Article | LibreCat-ID: 10314
Busa-Fekete, R., Szörényi, B., Weng, P., Cheng, W., & Hüllermeier, E. (2014). Preference-Based Reinforcement Learning: evolutionary direct policy search using a preference-based racing algorithm. Machine Learning, 97(3), 327–351.
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2014 | Conference Paper | LibreCat-ID: 10295
Fürnkranz, J., Hüllermeier, E., Rudin, C., Slowinski, R., & Sanner, S. (2014). Preference Learning (Dagstuhl Seminar 14101) Dagstuhl Reports (Vol. 4, pp. 1–27).
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2014 | Journal Article | LibreCat-ID: 10308
Hüllermeier, E. (2014). Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization. Int. J. Approx. Reasoning, 55(7), 1519–1534.
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2014 | Journal Article | LibreCat-ID: 10315
Montanés, E., Senge, R., Barranquero, J., Quevedo, J. R., Del Coz, J. J., & Hüllermeier, E. (2014). Dependent binary relevance models for multi-label classification. Pattern Recognition, 47(3), 1494–1508.
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2014 | Journal Article | LibreCat-ID: 10310
Strickert, M., Bunte, K., Schleif, F.-M., & Hüllermeier, E. (2014). Correlation-based embedding of pairwise score data. Neurocomputing, 141, 97–109.
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2014 | Conference Paper | LibreCat-ID: 457
Jungmann, A., Mohr, F., & Kleinjohann, B. (2014). Applying Reinforcement Learning for Resolving Ambiguity in Service Composition. In Proceedings of the 7th International Conference on Service Oriented Computing and Applications (SOCA) (pp. 105–112). https://doi.org/10.1109/SOCA.2014.48
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2014 | Conference Paper | LibreCat-ID: 10253
Schäfer, D., & Hüllermeier, E. (2014). Dyad Ranking Using A Bilinear Plackett-Luce Model. In Proceedings Lernen-Wissensentdeckung-Adaptivität (LWA), Aachen, Germany (pp. 32–33).
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2014 | Journal Article | LibreCat-ID: 10309
Hüllermeier, E. (2014). Rejoinder on "Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization. Int. J. Approx. Reasoning, 55(7), 1609–1613.
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2014 | Journal Article | LibreCat-ID: 10311
Senge, R., Bösner, S., Dembczynski, K., Haasenritter, J., Hirsch, O., Donner-Banzhoff, N., & Hüllermeier, E. (2014). Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty. Information Sciences, 255, 16–29.
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2014 | Journal Article | LibreCat-ID: 10316
Krempl, G., Zliobaite, I., Brzezinski, D., Hüllermeier, E., Last, M., Lemaire, V., … Stefanowski, J. (2014). Open challenges for data stream mining research. SIGKDD Explorations, 16(1), 1–10.
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