PUB - Publikationen an der Universität Bielefeld

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• [11]
  

  2016 | Preprint | Veröffentlicht | PUB-ID: 2901439

  Fischer, L., Villmann, T.: A Probabilistic Model with Adaptive Rejection. Machine Learning Reports, MLR-01-2016:1-19. (2016).

  PUB
   
• [10]
  

  2016 | Konferenzbeitrag | PUB-ID: 2905195

  Fischer, L., Hammer, B., Wersing, H.: Online Metric Learning for an Adaptation to Confidence Drift. Proceedings of International Joint Conference on Neural Networks (IJCNN). p. 748-755. IEEE, Vancouver (2016).

  PUB
   
• [9]
  

  2016 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2905193

  Fischer, L., Hammer, B., Wersing, H.: Optimal local rejection for classifiers. Neurocomputing. 214, 445-457 (2016).

  PUB | DOI | WoS
   
• [8]
  

  2016 | Bielefelder E-Dissertation | PUB-ID: 2906747

  Fischer, L.: Rejection and online learning with prototype-based classifiers in adaptive metrical spaces. Universität Bielefeld, Bielefeld (2016).

  PUB | PDF
   
• [7]
  

  2015 | Preprint | PUB-ID: 2774656

  Fischer, L., Hammer, B., Wersing, H.: Optimum Reject Options for Prototype-based Classification. (2015).

  PUB | arXiv
   
• [6]
  

  2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2774707

  Fischer, L., Hammer, B., Wersing, H.: Certainty-based Prototype Insertion/Deletion for Classification with Metric Adaptation. ESANN, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. p. 7-12. (2015).

  PUB
   
• [5]
  

  2015 | Konferenzbeitrag | PUB-ID: 2774721

  Fischer, L., Hammer, B., Wersing, H.: Combining Offline and Online Classifiers for Life-long Learning. IJCNN, International Joint Conference on Neural Networks. p. 2808-2815. (2015).

  PUB
   
• [4]
  

  2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2772413

  Fischer, L., Hammer, B., Wersing, H.: Efficient rejection strategies for prototype-based classification. Neurocomputing. 169, 334-342 (2015).

  PUB | DOI | WoS
   
• [3]
  

  2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2774643

  Fischer, L., Nebel, D., Villmann, T., Hammer, B., Wersing, H.: Rejection Strategies for Learning Vector Quantization – A Comparison of Probabilistic and Deterministic Approaches. In: Villmann, T., Schleif, F.-M., Kaden, M., and Lange, M. (eds.) Advances in Self-Organizing Maps and Learning Vector Quantization. Advances in Intelligent Systems and Computing. 295, p. 109-118. Springer International Publishing, Cham (2014).

  PUB | DOI
   
• [2]
  

  2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2673548

  Fischer, L., Hammer, B., Wersing, H.: Rejection strategies for learning vector quantization. In: Verleysen, M. (ed.) ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. p. 41-46. i6doc.com, Bruges, Belgium (2014).

  PUB
   
• [1]
  

  2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2774498

  Fischer, L., Hammer, B., Wersing, H.: Local Rejection Strategies for Learning Vector Quantization. In: Wermter, S., Weber, C., Duch, W., Honkela, T., Koprinkova-Hristova, P., Magg, S., Palm, G., and Villa, A.E.P. (eds.) Artificial Neural Networks and Machine Learning – ICANN 2014. Lecture Notes in Computer Science. 8681, p. 563-570. Springer International Publishing, Cham (2014).

  PUB | DOI