Please note that LibreCat no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
5947 Publications
2013 | Conference Paper | LibreCat-ID: 15162
S. Böttcher, A. Bültmann, R. Hartel, and J. Schlüßler, “Implementing Efficient Updates in Compressed Big Text Databases,” in International Conference on Database and Expert Systems Applications, 2013, pp. 189–202.
LibreCat
2013 | Journal Article | LibreCat-ID: 16044
D. Heider, R. Senge, W. Cheng, and E. Hüllermeier, “Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistence prediction,” Bioinformatics, vol. 29, no. 16, pp. 1946–1952, 2013.
LibreCat
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.
LibreCat
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.
LibreCat
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.
LibreCat
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.
LibreCat
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.
LibreCat
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.
LibreCat
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.
LibreCat
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.
LibreCat
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.
LibreCat
2013 | Conference Paper | LibreCat-ID: 13645
T. Graf, L. Schäfers, and M. Platzner, “On Semeai Detection in Monte-Carlo Go.,” in Proceedings of the International Conference on Computers and Games (CG), 2013.
LibreCat
2013 | Book Chapter | LibreCat-ID: 46385
H. V. Sosa, O. Schütze, G. Rudolph, and H. Trautmann, “The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume,” in EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV, vol. 227, M. Emmerich, A. Deutz, O. Schuetze, T. Bäck, A. Tantar, P. Moral, P. Legrand, P. Bouvry, and C. Coello, Eds. Springer International Publishing, 2013, pp. 189–205.
LibreCat
| DOI
2013 | Book Chapter | LibreCat-ID: 46386
H. Trautmann, G. Rudolph, C. Dominguez-Medina, and O. Schütze, “Finding Evenly Spaced Pareto Fronts for Three-Objective Optimization Problems,” in EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II, vol. 175, O. Schütze, C. C. Coello, A. Tantar, E. Tantar, P. Bouvry, M. P. Del, and P. Legrand, Eds. Springer Berlin Heidelberg, 2013, pp. 89–105.
LibreCat
| DOI