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449 Publications
2016 | Conference Paper | LibreCat-ID: 10222
Jasinska K, Dembczynski K, Busa-Fekete R, Klerx T, Hüllermeier E. Extreme F-measure maximization using sparse probability estimates . In: Balcan MF, Weinberger KQ, eds. Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA. ; 2016.
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2016 | Conference Paper | LibreCat-ID: 10223
Melnikov V, Hüllermeier E. Learning to aggregate using uninorms, in Proceedings ECML/PKDD-2016. In: European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy. ; 2016:756-771.
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2016 | Conference Paper | LibreCat-ID: 10224
Dembczynski K, Kotlowski W, Waegeman W, Busa-Fekete R, Hüllermeier E. Consistency of probalistic classifier trees. In: In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy. ; 2016:511-526.
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2016 | Conference Paper | LibreCat-ID: 10225
Shabani A, Paul A, Platon R, Hüllermeier E. Predicting the electricity consumption of buildings: An improved CBR approach. In: In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA. ; 2016:356-369.
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2016 | Conference Paper | LibreCat-ID: 10226
Pfannschmidt K, Hüllermeier E, Held S, Neiger R. 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. Springer; 2016:450-461.
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2016 | Conference Paper | LibreCat-ID: 10227
Labreuche C, Hüllermeier E, Vojtas P, Fallah Tehrani A. On the Identifiability of models in multi-criteria preference learning . In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. ; 2016.
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2016 | Conference Paper | LibreCat-ID: 10228
Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad Ranking. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. ; 2016.
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2016 | Conference Paper | LibreCat-ID: 10229
Couso I, Ahmadi Fahandar M, Hüllermeier E. Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. ; 2016.
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2016 | Conference Paper | LibreCat-ID: 10230
Lu S, Hüllermeier E. Support vector classification on noisy data using fuzzy supersets losses. In: Hoffmann F, Hüllermeier E, Mikut R, eds. Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing. ; 2016:1-8.
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2016 | Conference Paper | LibreCat-ID: 10231
Schäfer D, Hüllermeier E. Plackett-Luce networks for dyad ranking. In: In Workshop LWDA “Lernen, Wissen, Daten, Analysen.” ; 2016.
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2016 | Conference (Editor) | LibreCat-ID: 10263
Kaminka GA, Fox M, Bouquet P, et al., eds. ECAI 2016, 22nd European Conference on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence. Vol 285. The Hague, The Netherlands: IOS Press; 2016.
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2016 | Journal Article | LibreCat-ID: 10264
Leinweber M, Fober T, Strickert M, et al. CavSimBase: A database for large scale comparison of protein binding sites. IEEE Transactions on Knowledge and Data Engineering. 2016;28(6):1423-1434.
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2016 | Journal Article | LibreCat-ID: 10266
Riemenschneider M, Senge R, Neumann U, Hüllermeier E, Heider D. Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification. BioData Mining. 2016;9(10).
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2015 | Conference Paper | LibreCat-ID: 280
Arifulina S, Platenius MC, Mohr F, Engels G, Schäfer W. 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. ; 2015:333--340. doi:10.1109/SERVICES.2015.58
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2015 | Journal Article | LibreCat-ID: 323
Jungmann A, Mohr F. An approach towards adaptive service composition in markets of composed services. Journal of Internet Services and Applications. 2015;(1):1-18. doi:10.1186/s13174-015-0022-8
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2015 | Conference Paper | LibreCat-ID: 324
Mohr F. A Metric for Functional Reusability of Services. In: Proceedings of the 14th International Conference on Software Reuse (ICSR). LNCS. ; 2015:298--313. doi:10.1007/978-3-319-14130-5_21
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2015 | Conference Paper | LibreCat-ID: 319
Mohr F, Jungmann A, Kleine Büning H. Automated Online Service Composition. In: Proceedings of the 12th IEEE International Conference on Services Computing (SCC). ; 2015:57--64. doi:10.1109/SCC.2015.18
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2015 | Journal Article | LibreCat-ID: 4792
Senge R, Hüllermeier E. Fast Fuzzy Pattern Tree Learning for Classification. IEEE Transactions on Fuzzy Systems. 2015;23(6):2024-2033. doi:10.1109/tfuzz.2015.2396078
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2015 | Conference Paper | LibreCat-ID: 15406
Schäfer D, Hüllermeier E. 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. ; 2015:110-111.
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2015 | Conference Paper | LibreCat-ID: 15749
Paul A, Hüllermeier E. A cbr approach to the angry birds game. In: In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany. ; 2015:68-77.
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