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21 Publikationen

2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914505
Paaßen, B., Schulz, A., Hahne, J., & Hammer, B. (2018). Expectation maximization transfer learning and its application for bionic hand prostheses. Neurocomputing, 298, 122-133. doi:10.1016/j.neucom.2017.11.072
PUB | DOI | Download (ext.) | WoS | arXiv
 
2018 | Datenpublikation | PUB-ID: 2919994
Paaßen, B. (2018). Tree Edit Distance Learning via Adaptive Symbol Embeddings. Bielefeld University. doi:10.4119/unibi/2919994
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2018 | Datenpublikation | PUB-ID: 2916990
Paaßen, B. (2018). Median Generalized Learning Vector Quantization for Distance Data. Bielefeld University. doi:10.4119/unibi/2916990
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2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2919844
Paaßen, B., Gallicchio, C., Micheli, A., & Hammer, B. (2018). Tree Edit Distance Learning via Adaptive Symbol Embeddings. In J. Dy & A. Krause (Eds.), Proceedings of Machine Learning Research: Vol. 80. Proceedings of the 35th International Conference on Machine Learning (ICML 2018) (pp. 3973-3982).
PUB | Download (ext.) | arXiv
 
2017 | Datenpublikation | PUB-ID: 2912671
Paaßen, B., & Schulz, A. (2017). Linear Supervised Transfer Learning Toolbox. Bielefeld University. doi:10.4119/unibi/2912671
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2016 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2783224
Paaßen, B., Mokbel, B., & Hammer, B. (2016). Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. Neurocomputing, 192(SI), 3-13. doi:10.1016/j.neucom.2015.12.108
PUB | PDF | DOI | WoS
 
2015 | Bielefelder E-Dissertation | PUB-ID: 2733228
Zhu, X. (2015). Adaptive prototype-based dissimilarity learning. Bielefeld: Universitätsbibliothek Bielefeld.
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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
PUB | DOI | WoS
 
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2776021
Losing, V., Hammer, B., & Wersing, H. (2015). Interactive Online Learning for Obstacle Classification on a Mobile Robot. Presented at the International Joint Conference on Neural Networks, Killarney, Ireland. doi:10.1109/IJCNN.2015.7280610
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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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2013 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2622151
Giotis, I., Bunte, K., Petkov, N., & Biehl, M. (2013). Adaptive Matrices and Filters for Color Texture Classification. Journal Of Mathematical Imaging And Vision, 47(1-2), 79-92. doi:10.1007/s10851-012-0356-9
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2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2509858
Kaestner, M., Hammer, B., Biehl, M., & Villmann, T. (2012). Functional relevance learning in generalized learning vector quantization. Neurocomputing, 90, 85-95. doi:10.1016/j.neucom.2011.11.029
PUB | DOI | WoS
 
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2489405
Bunte, K., Schneider, P., Hammer, B., Schleif, F. - M., Villmann, T., & Biehl, M. (2012). Limited Rank Matrix Learning, discriminative dimension reduction and visualization. Neural Networks, 26, 159-173. doi:10.1016/j.neunet.2011.10.001
PUB | DOI | WoS | PubMed | Europe PMC
 
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1796195
Schneider, P., Biehl, M., & Hammer, B. (2010). Hyperparameter learning in probabilistic prototype-based models. Neurocomputing, 73(7-9), 1117-1124. doi:10.1016/j.neucom.2009.11.021
PUB | DOI | WoS
 
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1796189
Bunte, K., Hammer, B., Wismueller, A., & Biehl, M. (2010). Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data. Neurocomputing, 73(7-9), 1074-1092. doi:10.1016/j.neucom.2009.11.017
PUB | DOI | WoS
 
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1795962
Schneider, P., Bunte, K., Stiekema, H., Hammer, B., Villmann, T., & Biehl, M. (2010). Regularization in Matrix Relevance Learning. IEEE Transactions on Neural Networks, 21(5), 831-840. doi:10.1109/TNN.2010.2042729
PUB | DOI | WoS | PubMed | Europe PMC
 
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1969815
Denecke, A., Wersing, H., Steil, J. J., & Körner, E. (2009). Online figure-ground segmentation with adaptive metrics in Generalized LVQ. Neurocomputing, 72(7-9), 1470-1482. doi:10.1016/j.neucom.2008.11.028
PUB | DOI | WoS
 
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1969830
Kirstein, S., Denecke, A., Hasler, S., Wersing, H., Gross, H. - M., & Körner, E. (2009). A Vision Architecture for Unconstrained and Incremental Learning of Multiple Categories. Memetic Computing, 1(4), 291-304. doi:10.1007/s12293-009-0023-x
PUB | DOI
 
2001 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1617662
Heidemann, G., & Ritter, H. (2001). Efficient vector quantization using the WTA-rule with activity equalization. Neural Processing Letters, 13(1), 17-30. doi:10.1023/A:1009678928250
PUB | DOI | WoS
 

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