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428 Publications


2016 | Conference Paper | LibreCat-ID: 15403
Lu, S., & Hüllermeier, E. (2016). Support vector classification on noisy data using fuzzy superset losses. In E. Hüllermeier, F. Hoffmann, & R. Mikut (Eds.), in Proceedings 26th Workshop Computational Intelligence, Dortmund Germany (pp. 1–8). KIT Scientific Publishing.
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2016 | Journal Article | LibreCat-ID: 190
Platenius, M. C., Shaker, A., Becker, M., Hüllermeier, E., & Schäfer, W. (2016). Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic. IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017, (8), 739–759. https://doi.org/10.1109/TSE.2016.2632115
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2016 | Book Chapter | LibreCat-ID: 10214
Fürnkranz, J., & Hüllermeier, E. (2016). Preference Learning. In C. Sammut & G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining. Springer.
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2016 | Conference (Editor) | LibreCat-ID: 10221
Hoffmann, F., Hüllermeier, E., & Mikut, R. (Eds.). (2016). Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany.
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2016 | Conference Paper | LibreCat-ID: 10226
Pfannschmidt, K., Hüllermeier, E., Held, S., & Neiger, R. (2016). Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts. In In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands (pp. 450–461). Springer.
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2016 | Journal Article | LibreCat-ID: 10264
Leinweber, M., Fober, T., Strickert, M., Baumgärtner, L., Klebe, G., Freisleben, B., & Hüllermeier, E. (2016). CavSimBase: A database for large scale comparison of protein binding sites. IEEE Transactions on Knowledge and Data Engineering, 28(6), 1423–1434.
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2016 | Dissertation | LibreCat-ID: 141
Mohr, F. (2016). Towards Automated Service Composition Under Quality Constraints. Universität Paderborn. https://doi.org/10.17619/UNIPB/1-171
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2016 | Conference Paper | LibreCat-ID: 15404
Schäfer, D., & Hüllermeier, E. (2016). Plackett-Luce networks for dyad ranking. In in Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany.
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2016 | Journal Article | LibreCat-ID: 16041
Leinweber, M., Fober, T., Strickert, M., Baumgärtner, L., Klebe, G., Freisleben, B., & Hüllermeier, E. (2016). CavSimBase: A database for large scale comparison of protein binding sites. IEEE Transactions on Knowledge and Data Engineering, 28(6), 1423–1434.
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2016 | Conference Paper | LibreCat-ID: 184
Melnikov, V., & Hüllermeier, E. (2016). Learning to Aggregate Using Uninorms. In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016) (pp. 756–771). https://doi.org/10.1007/978-3-319-46227-1_47
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2016 | Conference Paper | LibreCat-ID: 10222
Jasinska, K., Dembczynski, K., Busa-Fekete, R., Klerx, T., & Hüllermeier, E. (2016). Extreme F-measure maximization using sparse probability estimates . In M. F. Balcan & K. Q. Weinberger (Eds.), Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA.
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2016 | Conference Paper | LibreCat-ID: 10227
Labreuche, C., Hüllermeier, E., Vojtas, P., & Fallah Tehrani, A. (2016). On the Identifiability of models in multi-criteria preference learning . In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning.
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2016 | Conference Paper | LibreCat-ID: 15400
Labreuche, C., Hüllermeier, E., Vojtas, P., & Fallah Tehrani, A. (2016). On the identifiability of models  in multi-criteria preference learning. In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.), in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany.
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2016 | Journal Article | LibreCat-ID: 3318
Melnikov, V., Hüllermeier, E., Kaimann, D., Frick, B., & Gupta, Pritha . (2016). Pairwise versus Pointwise Ranking: A Case Study. Schedae Informaticae, 25. https://doi.org/10.4467/20838476si.16.006.6187
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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.
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2015 | Conference Paper | LibreCat-ID: 10235
Hoffmann, F., & Hüllermeier, E. (2015). Proceedings 25. Workshop Computational Intelligence KIT Scientific Publishing.
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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: 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).
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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.
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2015 | Conference Paper | LibreCat-ID: 319
Mohr, F., Jungmann, A., & Kleine Büning, H. (2015). Automated Online Service Composition. In Proceedings of the 12th IEEE International Conference on Services Computing (SCC) (pp. 57--64). https://doi.org/10.1109/SCC.2015.18
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2015 | Journal Article | LibreCat-ID: 4792
Senge, R., & Hüllermeier, E. (2015). Fast Fuzzy Pattern Tree Learning for Classification. IEEE Transactions on Fuzzy Systems, 23(6), 2024–2033. https://doi.org/10.1109/tfuzz.2015.2396078
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2015 | Conference Paper | LibreCat-ID: 10236
Abdel-Aziz, A., & Hüllermeier, E. (2015). Case Base Maintenance in Preference-Based CBR. In In Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015) (pp. 1–14).
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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).
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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 | Conference Paper | LibreCat-ID: 15750
Ewerth, R., Balz, A., Gehlhaar, J., Dembczynski, K., & Hüllermeier, E. (2015). Depth estimation in monocular images: Quantitative versus qualitative approaches. In F. Hoffmann & E. Hüllermeier (Eds.), In Proceedings 25. Workshop Computational Intelligence, Dortmund, Germany (pp. 235–240). KIT Scientific Publishing.
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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: 16051
Hüllermeier, E. (2015). From knowledge-based to data driven fuzzy modeling: Development, criticism and alternative directions. Informatik Spektrum, 38(6), 500–509.
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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: 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 | 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: 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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2015 | Conference Paper | LibreCat-ID: 15749
Paul, A., & Hüllermeier, E. (2015). A cbr approach to the angry birds game. In In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany (pp. 68–77).
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2015 | Conference Paper | LibreCat-ID: 15751
Lu, S., & Hüllermeier, E. (2015). Locally weighted regression through data imprecisiation. In F. Hoffmann & E. Hüllermeier (Eds.), in Proceedings 25th Workshop Computational Intelligence, Dortmund Germany (pp. 97–104). KIT Scientific Publishing.
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2015 | Journal Article | LibreCat-ID: 323
Jungmann, A., & Mohr, F. (2015). An approach towards adaptive service composition in markets of composed services. Journal of Internet Services and Applications, (1), 1–18. https://doi.org/10.1186/s13174-015-0022-8
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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: 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).
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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 | Journal Article | LibreCat-ID: 10322
Hüllermeier, E. (2015). From Knowledge-based to Data-driven fuzzy modeling-Development, criticism and alternative directions. Informatik Spektrum, 38(6), 500–509.
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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 | Conference Paper | LibreCat-ID: 280
Arifulina, S., Platenius, M. C., Mohr, F., Engels, G., & Schäfer, W. (2015). Market-Specific Service Compositions: Specification and Matching. In Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet (pp. 333--340). https://doi.org/10.1109/SERVICES.2015.58
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2015 | Conference Paper | LibreCat-ID: 324
Mohr, F. (2015). A Metric for Functional Reusability of Services. In Proceedings of the 14th International Conference on Software Reuse (ICSR) (pp. 298--313). https://doi.org/10.1007/978-3-319-14130-5_21
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2015 | Journal Article | LibreCat-ID: 10323
Garcia-Jimenez, S., Bustince, U., Hüllermeier, E., Mesiar, R., Pal, N. R., & Pradera, A. (2015). Overlap Indices: Construction of and Application of Interpolative Fuzzy Systems. IEEE Transactions on Fuzzy Systems, 23(4), 1259–1273.
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2015 | Conference Paper | LibreCat-ID: 10234
Hüllermeier, E., & Minor, M. (2015). Case-Based Reasoning Research and Development . In in Proceedings 23rd International Conference on Case-Based Reasoning (ICCBR 2015) LNAI 9343. Springer.
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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).
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2015 | Conference Paper | LibreCat-ID: 10241
Szörényi, B., Busa-Fekete, R., Paul, A., & Hüllermeier, E. (2015). Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach. In in Advances in Neural Information Processing Systems 28 (NIPS 2015) (pp. 604–612).
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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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2014 | Journal Article | LibreCat-ID: 10297
Hoffmann, F., Hüllermeier, E., & Kroll, A. (2014). Ausgewählte Beiträge des GMA-Fachausschusses 5.14. Computational Intelligence Automatisierungstechnik, 62(10), 685–686.
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2014 | Journal Article | LibreCat-ID: 10312
Mernberger, M., Moog, M., Stork, S., Zauner, S., Maier, U. G., & Hüllermeier, E. (2014). Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances. J. Bioinformatics and Computational Biology, 12(1).
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2014 | Journal Article | LibreCat-ID: 10317
Krotzky, T., Fober, T., Hüllermeier, E., & Klebe, G. (2014). Extended Graph-Based Models for Enhanced Similarity Search in Cavbase. IEEE/ACM Trans. Comput. Biology Bioinform., 11(5), 878–890.
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