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1748 Publications
2015 | Conference Paper | LibreCat-ID: 10242
Szörényi, B., Busa-Fekete, R., Dembczynski, K., & Hüllermeier, E. (2015). Online F-Measure Optimization. In in Advances in Neural Information Processing Systems 28 (NIPS 2015) (pp. 595–603).
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2015 | Conference Paper | LibreCat-ID: 10243
El Mesaoudi-Paul, A., & Hüllermeier, E. (2015). A CBR Approach to the Angry Birds Game. In in Workshop Proc. 23rd International Conference on Case-Based Reasoning (ICCBR 2015) (pp. 68–77).
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).
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2015 | Conference Paper | LibreCat-ID: 10245
Lu, S., & Hüllermeier, E. (2015). Locally weighted regression through data imprecisiation. In Proceedings 25. Workshop Computational Intelligence (pp. 97–104).
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2015 | Conference Paper | LibreCat-ID: 10246
Ewerth, R., Balz, A., Gehlhaar, J., Dembczynski, K., & Hüllermeier, E. (2015). Depth estimation in monocular images: Quantitative versus qualitative approaches. In Proceedings 25. Workshop Computational Intelligence (pp. 235–240).
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2015 | Dissertation | LibreCat-ID: 10293
Meier, C. (2015). IT Project Portfolio Selection in the Presence of Project Interactions. Universität Paderborn.
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2015 | Dissertation | LibreCat-ID: 10294
Mutter, T. (2015). On the Activating Power of Gamification – Empirical Evidence from an Online Community. Universität Paderborn.
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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.
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2015 | Journal Article | LibreCat-ID: 10320
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: 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.
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