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2185 Publications
2015 | Conference Paper | LibreCat-ID: 15406
Schäfer, D., & Hüllermeier, E. (2015). Preference-based meta-learning using dyad ranking: Recommending algorithms in cold-start situations. In in Proceedings of the 2015 international Workshop on Meta-Learning and Algorithm Selection co-located ECML/PKDD, Porto, Portugal (pp. 110–111).
LibreCat
2015 | Journal Article | LibreCat-ID: 14879
Chen, W.-F., Chen, M.-H., Chen, M.-L., & Ku, L.-W. (2015). A Computer-assistance Learning System for Emotional Wording. IEEE Transactions on Knowledge and Data Engineering, 28(5), 1093–1104.
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2015 | Journal Article | LibreCat-ID: 16049
Senge, R., & Hüllermeier, E. (2015). Fast fuzzy pattern tree learning for classification . IEEE Transactions on Fuzzy Systems, 23(6), 2024–2033.
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2015 | Journal Article | LibreCat-ID: 16053
Hüllermeier, E. (2015). Does machine learning need fuzzy logic? Fuzzy Sets and Systems, 281, 292–299.
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2015 | Journal Article | LibreCat-ID: 16058
Waegeman, W., Dembczynski, K., Jachnik, A., Cheng, W., & Hüllermeier, E. (2015). On the Bayes-optimality of F-measure maximizers. Journal of Machine Learning Research, 15, 3313–3368.
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2015 | Journal Article | LibreCat-ID: 16067
Shaker, A., & Hüllermeier, E. (2015). Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study. Neurocomputing, 150, 250–264.
LibreCat
2015 | Conference Paper | LibreCat-ID: 1636
Auroux, S., Draxler, M., Morelli, A., & Mancuso, V. (2015). Dynamic network reconfiguration in wireless DenseNets with the CROWD SDN architecture. In 2015 European Conference on Networks and Communications (EuCNC). IEEE. https://doi.org/10.1109/eucnc.2015.7194057
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2015 | Journal Article | LibreCat-ID: 13964
Beutner, M., Pechuel, R., & Teine, M. (2015). Didaktische und organisatorische Strukturierungen von Micro-Learning – Konzeption und Umsetzungsbeispiele aus den OPALESCE Learning Units. Kölner Zeitschrift für Wirtschaft und Pädagogik, 81–128.
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2015 | Conference Paper | LibreCat-ID: 13153
Graf, T., & Platzner, M. (2015). Adaptive Playouts in Monte-Carlo Tree Search with Policy-Gradient Reinforcement Learning. In Advances in Computer Games: 14th International Conference, ACG 2015, Leiden, The Netherlands, July 1-3, 2015, Revised Selected Papers (pp. 1–11). Springer International Publishing. https://doi.org/10.1007/978-3-319-27992-3_1
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2015 | Conference Paper | LibreCat-ID: 10237
Szörényi, B., Busa-Fekete, R., Weng, P., & Hüllermeier, E. (2015). Qualitative Multi-Armed Bandits: A Quantile-Based Approach. In In Proceedings International Conference on Machine Learning (ICML 2015) (pp. 1660–1668).
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2015 | Conference Paper | LibreCat-ID: 10238
Schäfer, D., & Hüllermeier, E. (2015). Dyad Ranking Using A Bilinear Plackett-Luce Model. In in Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD) (pp. 227–242).
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2015 | Conference Paper | LibreCat-ID: 10239
Hüllermeier, E., & Cheng, W. (2015). Superset Learning Based on Generalized Loss Minimization . In in Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD) (pp. 260–275).
LibreCat
2015 | Conference Paper | LibreCat-ID: 10240
Henzgen, S., & Hüllermeier, E. (2015). Weighted Rank Correlation : A Flexible Approach Based on Fuzzy Order Relations. In in Proceedings European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD) (pp. 422–437).
LibreCat
2015 | Conference Paper | LibreCat-ID: 10244
Schäfer, D., & Hüllermeier, E. (2015). Preference-Based Meta- Learning Using Dyad Ranking: Recommending Algorithms in Cold-Start Situations. In in Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection (MetaSel@PKDD/ECML) (pp. 110–111).
LibreCat
2015 | Journal Article | LibreCat-ID: 10319
Waegeman, W., Dembczynski, K., Jachnik, A., Cheng, W., & Hüllermeier, E. (2015). On the Bayes-Optimality of F-Measure Maximizers. In Journal of Machine Learning Research, 15, 3333–3388.
LibreCat
2015 | Journal Article | LibreCat-ID: 10320
Hüllermeier, E. (2015). Does machine learning need fuzzy logic? Fuzzy Sets and Systems, 281, 292–299.
LibreCat
2015 | Journal Article | LibreCat-ID: 10321
Shaker, A., & Hüllermeier, E. (2015). Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study. Neurocomputing, 150, 250–264.
LibreCat
2015 | Journal Article | LibreCat-ID: 10324
Senge, R., & Hüllermeier, E. (2015). Fast Fuzzy Pattern Tree Learning of Classification. IEEE Transactions on Fuzzy Systems, 23(6), 2024–2033.
LibreCat
2015 | Journal Article | LibreCat-ID: 13502
Klein, C., Vollmers, N. J., Gerstmann, U., Zahl, P., Lükermann, D., Jnawali, G., … Horn-von Hoegen, M. (2015). Barrier-free subsurface incorporation of 3d metal atoms into Bi(111) films. Physical Review B, 91(19). https://doi.org/10.1103/physrevb.91.195441
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2015 | Conference Paper | LibreCat-ID: 30603
Paradkar, M., & Böcker, J. (2015). 3D analytical model for estimation of eddy currentlosses in the magnets of IPM machine considering the reaction field of the induced eddy currents. 2015 IEEE Energy Conversion Congress and Exposition (ECCE). https://doi.org/10.1109/ecce.2015.7310061
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