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6 Publikationen

2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2710031
Mokbel, B., Paaßen, B., Schleif, F. - M., & Hammer, B. (2015). Metric learning for sequences in relational LVQ. Neurocomputing, 169(SI), 306-322. doi:10.1016/j.neucom.2014.11.082
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2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2772407
Nebel, D., Hammer, B., Frohberg, K., & Villmann, T. (2015). Median variants of learning vector quantization for learning of dissimilarity data. Neurocomputing, 169(SI), 295-305. doi:10.1016/j.neucom.2014.12.096
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2015 | Bielefelder Masterarbeit | PUB-ID: 2736686
Paaßen, B. (2015). Adaptive Affine Sequence Alignment Using Algebraic Dynamic Programming. Bielefeld: Bielefeld University.
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2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2673554
Mokbel, B., Paaßen, B., & Hammer, B. (2014). Adaptive distance measures for sequential data. In M. Verleysen (Ed.), ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (pp. 265-270). Bruges, Belgium: i6doc.com.
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2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2710067
Mokbel, B., Paaßen, B., & Hammer, B. (2014). Efficient Adaptation of Structure Metrics in Prototype-Based Classification. In S. Wermter, C. Weber, W. Duch, T. Honkela, P. Koprinkova-Hristova, S. Magg, G. Palm, et al. (Eds.), Lecture Notes in Computer Science: Vol. 8681. Artificial Neural Networks and Machine Learning - ICANN 2014 - 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014. Proceedings (pp. 571-578). Springer. doi:10.1007/978-3-319-11179-7_72
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2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2509852
Zhu, X., Gisbrecht, A., Schleif, F. - M., & Hammer, B. (2012). Approximation techniques for clustering dissimilarity data. Neurocomputing, 90, 72-84. doi:10.1016/j.neucom.2012.01.033
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