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402 Publications


2014 | Journal Article | LibreCat-ID: 16082
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 | 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: 447
Jungmann, A., Mohr, F., & Kleinjohann, B. (2014). Combining Automatic Service Composition with Adaptive Service Recommendation for Dynamic Markets of Services. In Proceedings of the 10th World Congress on Services (SERVICES) (pp. 346–353). https://doi.org/10.1109/SERVICES.2014.68
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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 | 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 | 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 | Journal Article | LibreCat-ID: 16064
Hüllermeier, E. (2014). Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization. International Journal of Approximate Reasoning, 55(7), 1519–1534.
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2014 | Journal Article | LibreCat-ID: 16069
Henzgen, S., Strickert, M., & Hüllermeier, E. (2014). Visualization of evolving fuzzy-rule-based systems. Evolving Systems, 5, 175–191.
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2014 | Journal Article | LibreCat-ID: 16083
Donner-Banzhoff, N., Haasenritter, J., Hüllermeier, E., Viniol, A., Bösner, S., & Becker, A. (2014). The comprehensive diagnostic study is suggested as a design to model the diagnostic process. Journal of Clinical Epidemiology, 2(67), 124–132.
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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: 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 | 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: 16046
Agarwal, M., Fallah Tehrani, A., & Hüllermeier, E. (2014). Preference-based learning of ideal solutions in TOPSIS-like decision models. Journal of Multi-Criteria Decision Analysis, 22(3–4).
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2014 | Journal Article | LibreCat-ID: 16060
Krotzky, T., Fober, T., Hüllermeier, E., & Klebe, G. (2014). Extended graph-based models for enhanced similarity search in Cabase. IEEE/ACM Transactions of Computational Biology and Bioinformatics, 11(5), 878–890.
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2014 | Journal Article | LibreCat-ID: 16077
Busa-Fekete, R., Szörenyi, 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.
LibreCat
 

2014 | Journal Article | LibreCat-ID: 10296
Shaker, A., & Hüllermeier, E. (2014). Survival analysis on data streams: Analyzing temporal events in dynamically changing environments. Applied Mathematics and Computer Science, 24(1), 199–212.
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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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