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449 Publications


2016 | Conference Paper | LibreCat-ID: 15400
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. In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany. ; 2016.
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2016 | Conference Paper | LibreCat-ID: 15401
Schäfer D, Hüllermeier E. Preference -based reinforcement learning using dyad ranking. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. In Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany. ; 2016.
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2016 | Conference Paper | LibreCat-ID: 15402
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. In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany. ; 2016.
LibreCat
 

2016 | Conference Paper | LibreCat-ID: 15403
Lu S, Hüllermeier E. Support vector classification on noisy data using fuzzy superset losses. In: Hüllermeier E, Hoffmann F, Mikut R, eds. In Proceedings 26th Workshop Computational Intelligence, Dortmund Germany. KIT Scientific Publishing; 2016:1-8.
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2016 | Conference Paper | LibreCat-ID: 15404
Schäfer D, Hüllermeier E. Plackett-Luce networks for dyad ranking. In: In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany. ; 2016.
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2016 | Conference Paper | LibreCat-ID: 15111
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.
LibreCat
 

2016 | Journal Article | LibreCat-ID: 16041
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 | Dissertation | LibreCat-ID: 141
Mohr F. Towards Automated Service Composition Under Quality Constraints. Universität Paderborn; 2016. doi:10.17619/UNIPB/1-171
LibreCat | DOI
 

2016 | Book Chapter | LibreCat-ID: 10214
Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds. Encyclopedia of Machine Learning and Data Mining. Springer; 2016.
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2016 | Conference (Editor) | LibreCat-ID: 10221
Hoffmann F, Hüllermeier E, Mikut R, eds. Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany.; 2016.
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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.
LibreCat
 

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.
LibreCat
 

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.
LibreCat
 

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.
LibreCat
 

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.
LibreCat
 

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.
LibreCat
 

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.
LibreCat
 

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.
LibreCat
 

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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