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449 Publications


2013 | Journal Article | LibreCat-ID: 16081
S. Bösner, K. Bönisch, J. Haasenritter , P. Schlegel, E. Hüllermeier, and N. Donner-Banzhoff, “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, vol. 14, no. 1, pp. 154–162, 2013.
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2013 | Journal Article | LibreCat-ID: 16086
J. Haasenritter et al., “Diagnose im Kontext - eine erweiterte Perspektive,” Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen (ZEFQ), vol. 107, pp. 585–591, 2013.
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2013 | Journal Article | LibreCat-ID: 16123
A. Shaker, R. Senge, and E. Hüllermeier, “Evolving fuzzy pattern trees for binary classification on data streams,” Information Sciences, vol. 220, pp. 34–45, 2013.
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2013 | Conference Paper | LibreCat-ID: 13115
G. Szarvas, R. Busa-Fekete, and E. Hüllermeier, “Learning to rank lexical substitutions,” in In Proceedings EMNLP-2013 Conference on Empirical Methods in Natural Language Processing, Seattle, USA, 2013.
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2013 | Conference Paper | LibreCat-ID: 13116
K. Dembczynski, A. Jachnik, W. Kotlowski, W. Waegeman, and E. Hüllermeier, “Optimizing the F-measure in multi-label classification: Plug-in rule approach versus structured loss minimization,” in in Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, 2013, pp. 1130–1138.
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2013 | Conference Paper | LibreCat-ID: 13117
R. Busa-Fekete, B. Szoreny, P. Weng, W. Cheng, and E. Hüllermeier, “Top-k selection based on adaptive sampling of noisy preferences,” in in Proceedings ICML-2013, 30th International Conference on Machine Learning, Atlanta, USA, 2013, pp. 1094–1102.
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2013 | Conference Paper | LibreCat-ID: 13118
E. Hüllermeier and W. Cheng, “Preference-based CBR: General ideas and basic principles,” in in Proceedings IJCAI-13, 23rd international Joint Conference on Artificial Intelligence, Beijing, China, 2013, pp. 3012–3016.
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2013 | Conference Paper | LibreCat-ID: 13119
S. Henzgen, M. Strickert, and E. Hüllermeier, “Rule chains for visualizing evolving fuzzy rule-based systems,” in in Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland, 2013, pp. 279–288.
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2013 | Conference Paper | LibreCat-ID: 13190
A. Shaker and E. Hüllermeier, “Recovery analysis for adaptive learning from non-stationary data streams,” in in Proceedings CORES 2013, 8th International Conference on Computer Recognition Systems, Wroclaw, Poland, 2013, pp. 289–298.
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2012 | Conference Paper | LibreCat-ID: 15299
M. Leinweber et al., “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, 2012.
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