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2035 Publications
    2014 |  Journal Article | LibreCat-ID: 10299 
    
      S. Henzgen, M. Strickert, and E. Hüllermeier, “Visualization of evolving fuzzy rule-based systems,” Evolving Systems, vol. 5, no. 3, pp. 175–191, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10308 
    
      E. Hüllermeier, “Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization,” Int. J. Approx. Reasoning, vol. 55, no. 7, pp. 1519–1534, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10309 
    
      E. Hüllermeier, “Rejoinder on "Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization,” Int. J. Approx. Reasoning, vol. 55, no. 7, pp. 1609–1613, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10310 
    
      M. Strickert, K. Bunte, F.-M. Schleif, and E. Hüllermeier, “Correlation-based embedding of pairwise score data,” Neurocomputing, vol. 141, pp. 97–109, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10311 
    
      R. Senge et al., “Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty,” Information Sciences, vol. 255, pp. 16–29, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10312 
    
      M. Mernberger, M. Moog, S. Stork, S. Zauner, U. G. Maier, and E. Hüllermeier, “Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances,” J. Bioinformatics and Computational Biology, vol. 12, no. 1, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10313 
    
      T. Calders, F. Esposito, E. Hüllermeier, and R. Meo, “Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track,” Machine Learning, vol. 97, no. 1–2, pp. 1–3, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10314 
    
      R. Busa-Fekete, B. Szörényi, P. Weng, W. Cheng, and E. Hüllermeier, “Preference-Based Reinforcement Learning: evolutionary direct policy search using a preference-based racing algorithm,” Machine Learning, vol. 97, no. 3, pp. 327–351, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10315 
    
      E. Montanés, R. Senge, J. Barranquero, J. R. Quevedo, J. J. Del Coz, and E. Hüllermeier, “Dependent binary relevance models for multi-label classification,” Pattern Recognition, vol. 47, no. 3, pp. 1494–1508, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10316 
    
      G. Krempl et al., “Open challenges for data stream mining research,” SIGKDD Explorations, vol. 16, no. 1, pp. 1–10, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10317 
    
      T. Krotzky, T. Fober, E. Hüllermeier, and G. Klebe, “Extended Graph-Based Models for Enhanced Similarity Search in Cavbase,” IEEE/ACM Trans. Comput. Biology Bioinform., vol. 11, no. 5, pp. 878–890, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 10318 
    
      M. Stock et al., “Identification of Functionally Releated Enzymes by Learning to Rank Methods,” IEEE/ACM Trans. Comput. Biology Bioinform., vol. 11, no. 6, pp. 1157–1169, 2014.
    
    
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    2014 |  Journal Article | LibreCat-ID: 13510 
    
      A. Hoffmann, M. Rohrmüller, A. Jesser, I. dos Santos Vieira, W. G. Schmidt, and S. Herres-Pawlis, “Geometrical and optical benchmarking of copper(II) guanidine-quinoline complexes: Insights from TD-DFT and many-body perturbation theory (part II),” Journal of Computational Chemistry, vol. 35, no. 29–30, pp. 2146–2161, 2014.
    
    
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