Jin L, Kang Y, Steffen E. Choosability in signed planar graphs. European J Combinatorics. 2016;52:234-243.
LibreCat: /record/10161

Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds. Encyclopedia of Machine Learning and Data Mining. Springer; 2016.
LibreCat: /record/10214

Hoffmann F, Hüllermeier E, Mikut R, eds.  Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany.; 2016.
LibreCat: /record/10221

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.
LibreCat: /record/10222

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: /record/10223

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: /record/10224

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: /record/10225

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: /record/10226

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 DPL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. ; 2016.
LibreCat: /record/10227

Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad Ranking. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. Proceedings DPL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. ; 2016.
LibreCat: /record/10228

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 DPL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. ; 2016.
LibreCat: /record/10229

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: /record/10230

Schäfer D, Hüllermeier E. Plackett-Luce networks for dyad ranking. In: In Workshop LWDA “Lernen, Wissen, Daten, Analysen.” ; 2016.
LibreCat: /record/10231

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.
LibreCat: /record/10263

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.
LibreCat: /record/10264

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).
LibreCat: /record/10266

John T. Business Model Modeling Languages as Tools for Innovation:  Theory and Empirical Evidence. Universität Paderborn; 2016. doi:10.17619/UNIPB/1-259 
LibreCat: /record/10292
DOI: 10.17619/UNIPB/1-259 

Abujoda A, Razzaghi Kouchaksaraei H, Papadimitriou P. SDN-Based Source Routing for Scalable Service Chaining in Datacenters. In: Springer International Publishing; 2016:66-77.
LibreCat: /record/1039

Timmer F, Oelke R, Dues C, et al. Strain-induced quasi-one-dimensional rare-earth silicide structures on Si(111). Physical Review B. 2016;94(20). doi:10.1103/physrevb.94.205431
LibreCat: /record/13475
DOI: 10.1103/physrevb.94.205431

Vollmers NJ, Müller P, Hoffmann A, et al. Experimental and Theoretical High-Energy-Resolution X-ray Absorption Spectroscopy: Implications for the Investigation of the Entatic State. Inorganic Chemistry. 2016;55:11694-11706. doi:10.1021/acs.inorgchem.6b01704
LibreCat: /record/13476
DOI: 10.1021/acs.inorgchem.6b01704