23 Publikationen
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2013 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982105Schleif, F.-M., Zhu, X., Hammer, B.: Sparse Prototype Representation by Core Sets. In: Yin, H., Tang, K., Gao, Y., Klawonn, F., Lee, M., Weise, T., Li, B., and Yao, X. (eds.) Intelligent Data Engineering and Automated Learning – IDEAL 2013. Lecture Notes in Computer Science. p. 302-309. Springer Berlin Heidelberg, Berlin, Heidelberg (2013).PUB | DOI
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2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625202Schleif, F.-M., Zhu, X., Hammer, B.: Sparse prototype representation by core sets. In: Hujun Yin, et.al (ed.) IDEAL 2013. (2013).PUB
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2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615717Zhu, X., Schleif, F.-M., Hammer, B.: Secure Semi-supervised Vector Quantization for Dissimilarity Data. In: Rojas, I., Joya, G., and Cabestany, J. (eds.) IWANN (1). Lecture Notes in Computer Science. 7902, p. 347-356. Springer (2013).PUB | DOI
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2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615701Zhu, X., Schleif, F.-M., Hammer, B.: Semi-Supervised Vector Quantization for proximity data. Proceedings of ESANN 2013. p. 89-94. (2013).PUB
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2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2625232Gisbrecht, A., Mokbel, B., Schleif, F.-M., Zhu, X., Hammer, B.: Linear Time Relational Prototype Based Learning. International Journal of Neural Systems. 22, : 1250021 (2012).PUB | DOI | WoS | PubMed | Europe PMC
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2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615750Schleif, F.-M., Zhu, X., Gisbrecht, A., Hammer, B.: Fast approximated relational and kernel clustering. Proceedings of ICPR 2012. p. 1229-1232. IEEE (2012).PUB
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2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2536437Gross, S., Zhu, X., Hammer, B., Pinkwart, N.: Cluster based feedback provision strategies in intelligent tutoring systems. Proceedings of the 11th international conference on Intelligent Tutoring Systems. p. 699-700. Springer-Verlag, Berlin, Heidelberg (2012).PUB | PDF | DOI | Download (ext.)
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2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982113Hammer, B., Gisbrecht, A., Hasenfuss, A., Mokbel, B., Schleif, F.-M., Zhu, X.: Topographic Mapping of Dissimilarity Data. In: Laaksonen, J. and Honkela, T. (eds.) Advances in Self-Organizing Maps. Lecture Notes in Computer Science. p. 1-15. Springer Berlin Heidelberg, Berlin, Heidelberg (2011).PUB | DOI
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2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982112Hammer, B., Schleif, F.-M., Zhu, X.: Relational Extensions of Learning Vector Quantization. In: Lu, B.-L., Zhang, L., and Kwok, J. (eds.) Neural Information Processing. Lecture Notes in Computer Science. p. 481-489. Springer Berlin Heidelberg, Berlin, Heidelberg (2011).PUB | DOI
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2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982111Hammer, B., Mokbel, B., Schleif, F.-M., Zhu, X.: Prototype-Based Classification of Dissimilarity Data. In: Gama, J., Bradley, E., and Hollmén, J. (eds.) Advances in Intelligent Data Analysis X. Lecture Notes in Computer Science. p. 185-197. Springer Berlin Heidelberg, Berlin, Heidelberg (2011).PUB | DOI
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2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276480Gisbrecht, A., Schleif, F.-M., Zhu, X., Hammer, B.: Linear time heuristics for topographic mapping of dissimilarity data. Intelligent Data Engineering and Automated Learning - IDEAL 2011: IDEAL 2011, 12th international conference, Norwich, UK, September 7 - 9, 2011 ; proceedings. Lecture Notes in Computer Science. 6936, p. 25-33. Springer, Berlin, Heidelberg (2011).PUB | DOI
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2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276485Hammer, B., Gisbrecht, A., Hasenfuss, A., Mokbel, B., Schleif, F.-M., Zhu, X.: Topographic Mapping of Dissimilarity Data. WSOM'11. (2011).PUB
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2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276522Gisbrecht, A., Hammer, B., Schleif, F.-M., Zhu, X.: Accelerating dissimilarity clustering for biomedical data analysis. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. p. pp.154-161. (2011).PUB
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2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2091665Zhu, X., Hammer, B.: Patch Affinity Propagation. Presented at the 19th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium (2011).PUB