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6112 Publications
2011 | Conference Paper | LibreCat-ID: 15116
E. Lughofer and E. Hüllermeier, “On-line redundancy deletion in evolving fuzzy regression models using a fuzzy inclusion measure,” in in Proceedings EUSFLAT-2011 7th International Conference on the European Society for Fuzzy Logic and Technology, Aix-les-Bains, France, 2011, pp. 380–387.
LibreCat
2011 | Conference Paper | LibreCat-ID: 15117
A. Fallah Tehrani, W. Cheng, and E. Hüllermeier, “Choquistic regression: Generalizing logistic regression using the Choquet integral,” in in Proceedings EUSFLAT-2011 7th International Conference on the European Society for Fuzzy Logic and Technology, Aix-les-Bains, France, 2011, pp. 868–875.
LibreCat
2011 | Conference Abstract | LibreCat-ID: 15181
S. Böttcher, R. Hartel, and H. Hawicks, “Namenlemmatisierung in der Web-Datenbank mittelalterlicher und frühneuzeitlicher Universitätsmatrikel,” in XXIV ICOS Internationales Kongress für Namensforschung, 2011.
LibreCat
2011 | Conference Paper | LibreCat-ID: 15193
G. Domik, S. Arens, I. Scharlau, and F. Hilkenmeier, “How useful is computer graphics for medical diagnoses?,” in INFORMATIK 2011 – Informatik schafft Communities, 2011, no. 324, p. 437.
LibreCat
2011 | Journal Article | LibreCat-ID: 16119
O. Hirsch, S. Bösner, E. Hüllermeier, R. Senge, K. Dembczynski, and N. Donner-Banzhoff, “Multivariate modeling to identify patterns in clinical data: The example of chest pain,” BMC Medical Research Methodology, vol. 11, no. 155, 2011.
LibreCat
2011 | Journal Article | LibreCat-ID: 16126
C. Domshlak, E. Hüllermeier, S. Kaci, and H. Prade, “Preferences in AL: An overview,” Artificial Intelligence, vol. 175, no. 7–8, pp. 1037–1052, 2011.
LibreCat
2011 | Journal Article | LibreCat-ID: 16147
E. Hüllermeier, “Fuzzy machine learning and data mining,” WIREs Data Mining and Knowledge Discovery, vol. 1, no. 4, pp. 269–283, 2011.
LibreCat
2011 | Journal Article | LibreCat-ID: 16148
M. Mernberger, G. Klebe, and E. Hüllermeier, “SEGA: Semi-global graph alignment for structure-based protein comparison,” IEEE/ACM Transactions of Computational Biology and Bioinformatics, vol. 8, no. 5, pp. 1330–1343, 2011.
LibreCat
2011 | Journal Article | LibreCat-ID: 16149
T. Fober, S. Glinca, G. Klebe, and E. Hüllermeier, “Superposition and alignment of labeled point clouds,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 6, pp. 1653–1666, 2011.
LibreCat
2011 | Journal Article | LibreCat-ID: 16150
E. Hüllermeier, “Fuzzy sets in machine learning and data mining,” Applied Soft Computing Journal, pp. 1493–1505, 2011.
LibreCat
2011 | Journal Article | LibreCat-ID: 16153
R. Senge and E. Hüllermeier, “Top-down induction of fuzzy pattern trees,” IEEE Transactions on Fuzzy Systems, vol. 19, no. 2, pp. 241–252, 2011.
LibreCat
2011 | Conference Paper | LibreCat-ID: 13194
K. Dembczynski, W. Waegeman, W. Cheng, and E. Hüllermeier, “An exact algorithm for F-measure maximization,” in In Proceedings NIPS-2011, 25th Annual Conference on Neural Information Processing Systems, Granada, Spain, 2011.
LibreCat
2011 | Conference Paper | LibreCat-ID: 13196
J. Fürnkranz and E. Hüllermeier, “Learning from label preferences,” in in Proceedings DS-2011, 14th International Conference on Discovery Science, number 6926 in LNAI, 2011, pp. 2–17.
LibreCat
2011 | Conference Paper | LibreCat-ID: 13197
A. Fallah Tehrani, W. Cheng, K. Dembczynski, and E. Hüllermeier, “Learning monotone nonlinear models using the Choquet integral,” in In Proceedings ECML/PKDD-2011, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Athens, Greece, 2011.
LibreCat
2011 | Conference Paper | LibreCat-ID: 13198
E. Hüllermeier and P. Schlegel, “Preference-based CBR: First steps toward a methodological framework,” in In Proceedings ICCBR-2011, 19th International Conference on Case-Based Reasoning, number 6880 in LNAI, 2011, pp. 77–91.
LibreCat
2011 | Conference Paper | LibreCat-ID: 13588
W. Kotlowski, K. Dembczynski, and E. Hüllermeier, “Bipartite ranking through minimization of univariate loss,” in in Proceedings ICML-2011, 28th International Conference on Machine Learning, Washington, USA, 2011.
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