Hägglund, Jonas, and Eckhard Steffen. “Petersen Colorings and Some Families of Snarks.” Ars Mathematica Contemporanea 312 (2014): 476–78.

Busa-Fekete, Robert, B. Szörényi, and Eyke Hüllermeier. “PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences.” In Proceedings AAAI 2014, Quebec, Canada, 1701–7, 2014.

Busa-Fekete, Robert, and Eyke Hüllermeier. “A Survey of Preference-Based Online Learning with Bandit Algorithms.” In Proceedings Int. Conf. on Algorithmic Learning Theory (ALT), Bled, Slovenia, 18–39, 2014.

Henzgen, Sascha, and Eyke Hüllermeier. “Mining Rank Data.” In Proceedings Discovery Science, Bled,Slovenia , 123–34, 2014.

Fallah Tehrani, A., M. Strickert, and Eyke Hüllermeier. “The Choquet Kernel for Monotone Data.” In Proceedings ESANN , Bruges, Belgium, 2014.

Abdel-Aziz, A., M. Strickert, and Eyke Hüllermeier. “Learning Solution Similarity in Preference-Based CBR.” In Proceedings Int. Conf. Case-Based Reasoning (ICCBR), Cork, Ireland, 17–31, 2014.

Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using A Bilinear Plackett-Luce Model.” In Proceedings Lernen-Wissensentdeckung-Adaptivität (LWA), Aachen, Germany, 32–33, 2014.

Calders, T., F. Esposito, Eyke Hüllermeier, and R. Meo. “Machine Learning and Knowledge Discovery in Databases-European Conf. ECML/PKDD, Nancy, France.” In Proceedings, Parts I-III. Lecture Notes in Computer Science, 8724–26. Springer, 2014.

Herrmann, Philipp. On Consumer Purchasing Behavior in Electronic Markets. Universität Paderborn, 2014.

Fürnkranz, J., Eyke Hüllermeier, Cynthia Rudin, Roman Slowinski, and Scott Sanner. “Preference Learning (Dagstuhl Seminar 14101) Dagstuhl Reports,” 4:1–27, 2014.

Shaker, Ammar, and Eyke Hüllermeier. “Survival Analysis on Data Streams: Analyzing Temporal Events in Dynamically Changing Environments.” Applied Mathematics and Computer Science 24, no. 1 (2014): 199–212.

Hoffmann, F., Eyke Hüllermeier, and A. Kroll. “Ausgewählte Beiträge Des GMA-Fachausschusses 5.14.” Computational Intelligence Automatisierungstechnik 62, no. 10 (2014): 685–86.

Calders, T., F. Esposito, Eyke Hüllermeier, and R. Meo. “Guest Editors`introduction:Special Issue of the ECML/PKDD 2014 Journal Track.” Data Min. Knowledge Discovery 28, no. 5–6 (2014): 1129–33.

Henzgen, Sascha, M. Strickert, and Eyke Hüllermeier. “Visualization of Evolving Fuzzy Rule-Based Systems.” Evolving Systems 5, no. 3 (2014): 175–91.

Hüllermeier, Eyke. “Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization.” Int. J. Approx. Reasoning 55, no. 7 (2014): 1519–34.

Hüllermeier, Eyke. “Rejoinder on "Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization.” Int. J. Approx. Reasoning 55, no. 7 (2014): 1609–13.

Strickert, M., K. Bunte, F.- M. Schleif, and Eyke Hüllermeier. “Correlation-Based Embedding of Pairwise Score Data.” Neurocomputing 141 (2014): 97–109.

Senge, Robin, S. Bösner, K. Dembczynski, J. Haasenritter, O. Hirsch, N. Donner-Banzhoff, and Eyke Hüllermeier. “Reliable Classification: Learning Classifiers That Distinguish Aleatoric and Epistemic Uncertainty.” Information Sciences 255 (2014): 16–29.

Mernberger, M., M. Moog, S. Stork, S. Zauner, U.G. Maier, and Eyke Hüllermeier. “Protein Sub-Cellular Localization Prediction for Special Compartments via Optimized Time Series Distances.” J. Bioinformatics and Computational Biology 12, no. 1 (2014).

Calders, T., F. Esposito, Eyke Hüllermeier, and R. Meo. “Guest Editors`introduction:Special Issue of the ECML/PKDD 2014 Journal Track.” Machine Learning 97, no. 1–2 (2014): 1–3.