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449 Publications


2013 | Journal Article | LibreCat-ID: 16081
Bösner, S., Bönisch, K., Haasenritter , J., Schlegel, P., Hüllermeier, E., & Donner-Banzhoff, N. (2013). 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, 14(1), 154–162.
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2013 | Journal Article | LibreCat-ID: 16086
Haasenritter, J., Viniol, A., Becker, A., Bösner, S., Hüllermeier, E., Senge, R., & Donner-Banzhoff, N. (2013). Diagnose im Kontext - eine erweiterte Perspektive. Zeitschrift Für Evidenz, Fortbildung Und Qualität Im Gesundheitswesen (ZEFQ), 107, 585–591.
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2013 | Journal Article | LibreCat-ID: 16123
Shaker, A., Senge, R., & Hüllermeier, E. (2013). Evolving fuzzy pattern trees for binary classification on data streams. Information Sciences, 220, 34–45.
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2013 | Conference Paper | LibreCat-ID: 13115
Szarvas, G., Busa-Fekete, R., & Hüllermeier, E. (2013). Learning to rank lexical substitutions. In In Proceedings EMNLP-2013 Conference on Empirical Methods in Natural Language Processing, Seattle, USA.
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2013 | Conference Paper | LibreCat-ID: 13116
Dembczynski, K., Jachnik, A., Kotlowski, W., Waegeman, W., & Hüllermeier, E. (2013). Optimizing the F-measure in multi-label classification: Plug-in rule approach versus structured loss minimization. In S. Dasgupta & D. McAllester (Eds.), in Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA (pp. 1130–1138).
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2013 | Conference Paper | LibreCat-ID: 13117
Busa-Fekete, R., Szoreny, B., Weng, P., Cheng, W., & Hüllermeier, E. (2013). Top-k selection based on adaptive sampling of noisy preferences. In S. Dasgupta & D. McAllester (Eds.), in Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA (pp. 1094–1102).
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2013 | Conference Paper | LibreCat-ID: 13118
Hüllermeier, E., & Cheng, W. (2013). Preference-based CBR: General ideas and basic principles. In F. Rossi (Ed.), in Proceedings IJCAI-13, 23rd international Joint Conference on Artificial Intelligence, Beijing, China (pp. 3012–3016). AAAI Press.
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2013 | Conference Paper | LibreCat-ID: 13119
Henzgen, S., Strickert, M., & Hüllermeier, E. (2013). Rule chains for visualizing evolving fuzzy rule-based systems. In R. Burduk, K. Jackowski, M. Kurzynski, M. Wozniak, & A. Zolnierek (Eds.), in Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland (pp. 279–288). Springer.
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2013 | Conference Paper | LibreCat-ID: 13190
Shaker, A., & Hüllermeier, E. (2013). Recovery analysis for adaptive learning from non-stationary data streams. In R. Burduk, K. Jackowski, M. Kurzynski, W. Wozniak, & A. Zolnierek (Eds.), in Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland (pp. 289–298). Springer.
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2012 | Conference Paper | LibreCat-ID: 15299
Leinweber, M., Baumgärtner, L., Mernberger, M., Fober, T., Hüllermeier, E., Klebe, G., & Freisleben, B. (2012). 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.
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