@inproceedings{10250,
  author       = {{Fallah Tehrani, A. and Strickert, M. and Hüllermeier, Eyke}},
  booktitle    = {{Proceedings ESANN , Bruges, Belgium}},
  title        = {{{The Choquet kernel for monotone data}}},
  year         = {{2014}},
}

@inproceedings{10251,
  author       = {{Abdel-Aziz, A. and Strickert, M. and Hüllermeier, Eyke}},
  booktitle    = {{Proceedings Int. Conf. Case-Based Reasoning (ICCBR), Cork, Ireland}},
  pages        = {{17--31}},
  title        = {{{Learning Solution Similarity in Preference-Based CBR}}},
  year         = {{2014}},
}

@inproceedings{10253,
  author       = {{Schäfer, Dirk and Hüllermeier, Eyke}},
  booktitle    = {{Proceedings Lernen-Wissensentdeckung-Adaptivität (LWA), Aachen, Germany}},
  pages        = {{32--33}},
  title        = {{{Dyad Ranking Using A Bilinear Plackett-Luce Model}}},
  year         = {{2014}},
}

@inproceedings{10254,
  author       = {{Calders, T. and Esposito, F. and Hüllermeier, Eyke and Meo, R.}},
  booktitle    = {{Proceedings, Parts I-III. Lecture Notes in Computer Science}},
  pages        = {{8724--8726}},
  publisher    = {{Springer}},
  title        = {{{Machine Learning and Knowledge Discovery in Databases-European Conf. ECML/PKDD, Nancy, France}}},
  year         = {{2014}},
}

@phdthesis{10291,
  author       = {{Herrmann, Philipp}},
  title        = {{{On Consumer Purchasing Behavior in Electronic Markets}}},
  year         = {{2014}},
}

@inproceedings{10295,
  author       = {{Fürnkranz, J. and Hüllermeier, Eyke and Rudin, Cynthia and Slowinski, Roman and Sanner, Scott}},
  number       = {{3}},
  pages        = {{1--27}},
  title        = {{{Preference Learning (Dagstuhl Seminar 14101) Dagstuhl Reports}}},
  volume       = {{4}},
  year         = {{2014}},
}

@article{10296,
  author       = {{Shaker, Ammar and Hüllermeier, Eyke}},
  journal      = {{Applied Mathematics and Computer Science}},
  number       = {{1}},
  pages        = {{199--212}},
  title        = {{{Survival analysis on data streams: Analyzing temporal events in dynamically changing environments}}},
  volume       = {{24}},
  year         = {{2014}},
}

@article{10297,
  author       = {{Hoffmann, F. and Hüllermeier, Eyke and Kroll, A.}},
  journal      = {{Computational Intelligence Automatisierungstechnik}},
  number       = {{10}},
  pages        = {{685--686}},
  title        = {{{Ausgewählte Beiträge des GMA-Fachausschusses 5.14}}},
  volume       = {{62}},
  year         = {{2014}},
}

@article{10298,
  author       = {{Calders, T. and Esposito, F. and Hüllermeier, Eyke and Meo, R.}},
  journal      = {{Data Min. Knowledge Discovery}},
  number       = {{5-6}},
  pages        = {{1129--1133}},
  title        = {{{Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track}}},
  volume       = {{28}},
  year         = {{2014}},
}

@article{10299,
  author       = {{Henzgen, Sascha and Strickert, M. and Hüllermeier, Eyke}},
  journal      = {{Evolving Systems}},
  number       = {{3}},
  pages        = {{175--191}},
  title        = {{{Visualization of evolving fuzzy rule-based systems}}},
  volume       = {{5}},
  year         = {{2014}},
}

@article{10308,
  author       = {{Hüllermeier, Eyke}},
  journal      = {{Int. J. Approx. Reasoning}},
  number       = {{7}},
  pages        = {{1519--1534}},
  title        = {{{Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization}}},
  volume       = {{55}},
  year         = {{2014}},
}

@article{10310,
  author       = {{Strickert, M. and Bunte, K. and Schleif, F.- M. and Hüllermeier, Eyke}},
  journal      = {{Neurocomputing}},
  pages        = {{97--109}},
  title        = {{{Correlation-based embedding of pairwise score data}}},
  volume       = {{141}},
  year         = {{2014}},
}

@article{10311,
  author       = {{Senge, Robin and Bösner, S. and Dembczynski, K. and Haasenritter, J. and Hirsch, O. and Donner-Banzhoff, N. and Hüllermeier, Eyke}},
  journal      = {{Information Sciences}},
  pages        = {{16--29}},
  title        = {{{Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty}}},
  volume       = {{255}},
  year         = {{2014}},
}

@article{10312,
  author       = {{Mernberger, M. and Moog, M. and Stork, S. and Zauner, S. and Maier, U.G. and Hüllermeier, Eyke}},
  journal      = {{J. Bioinformatics and Computational Biology}},
  number       = {{1}},
  title        = {{{Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances}}},
  volume       = {{12}},
  year         = {{2014}},
}

@article{10313,
  author       = {{Calders, T. and Esposito, F. and Hüllermeier, Eyke and Meo, R.}},
  journal      = {{Machine Learning}},
  number       = {{1-2}},
  pages        = {{1--3}},
  title        = {{{Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track}}},
  volume       = {{97}},
  year         = {{2014}},
}

@article{10314,
  author       = {{Busa-Fekete, Robert and Szörényi, B. and Weng, P. and Cheng, W. and Hüllermeier, Eyke}},
  journal      = {{Machine Learning}},
  number       = {{3}},
  pages        = {{327--351}},
  title        = {{{Preference-Based Reinforcement Learning: evolutionary direct policy search using a preference-based racing algorithm}}},
  volume       = {{97}},
  year         = {{2014}},
}

@article{10315,
  author       = {{Montanés, E. and Senge, Robin and Barranquero, J. and Quevedo, J.R. and Del Coz, J.J. and Hüllermeier, Eyke}},
  journal      = {{Pattern Recognition}},
  number       = {{3}},
  pages        = {{1494--1508}},
  title        = {{{Dependent binary relevance models for multi-label classification}}},
  volume       = {{47}},
  year         = {{2014}},
}

@article{10316,
  author       = {{Krempl, G. and Zliobaite, I. and Brzezinski, D. and Hüllermeier, Eyke and Last, M. and Lemaire, V. and Noack, T. and Shaker, Ammar and Sievi, S. and Spiliopoulou, M. and Stefanowski, J.}},
  journal      = {{SIGKDD Explorations}},
  number       = {{1}},
  pages        = {{1--10}},
  title        = {{{Open challenges for data stream mining research}}},
  volume       = {{16}},
  year         = {{2014}},
}

@article{10317,
  author       = {{Krotzky, T. and Fober, T. and Hüllermeier, Eyke and Klebe, G.}},
  journal      = {{IEEE/ACM Trans. Comput. Biology Bioinform.}},
  number       = {{5}},
  pages        = {{878--890}},
  title        = {{{Extended Graph-Based Models for Enhanced Similarity Search in Cavbase}}},
  volume       = {{11}},
  year         = {{2014}},
}

@article{10318,
  author       = {{Stock, M. and Fober, T. and Hüllermeier, Eyke and Glinca, S, and Klebe, G. and Pahikkala, T. and Airola, A. and De Baets, B. and Wageman, W.}},
  journal      = {{IEEE/ACM Trans. Comput. Biology Bioinform.}},
  number       = {{6}},
  pages        = {{1157--1169}},
  title        = {{{Identification of Functionally Releated Enzymes by Learning to Rank Methods}}},
  volume       = {{11}},
  year         = {{2014}},
}