197,255 research outputs found
Some Theoretical Aspects of the Neural Gas Vector Quantizer
No full textVillmann T, Hammer B, Biehl M. Some theoretical aspects of the neural gas vector quantizer. In: Biehl M, Hammer B, Verleysen M, Villmann T, eds. Similarity Based Clustering. Lecture Notes Artificial Intelligence, 5400. Berlin, Heidelberg: Springer; 2009: 23-34
Similarity-based Clustering and its Application to Medicine and Biology
Full text linkBiehl M, Hammer B, Verleysen M, Villmann T, eds. Similarity-based Clustering and its Application to Medicine and Biology. Vol 7131. Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI); 2007
Nonlinear discriminative data visualization
Full text linkBunte K, Biehl M, Hammer B. Nonlinear discriminative data visualization. In: Verleysen M, ed. European Symposium on Artificial Neural Networks. Evere: d-side publications; 2009: 65-70
Generalized Functional Relevance Learning Vector Quantization
Full text linkKaestner M, Hammer B, Biehl M, Villmann T. Generalized Functional Relevance Learning Vector Quantization. In: Verleysen M, ed. European Symposium on Artificial Neural Networks. D side; 2011: pp. 93-98
Metric Learning for Prototype-Based Classification
Full text linkBiehl M, Hammer B, Schneider P, Villmann T. Metric learning for prototype based classification. In: Bianchini M, Maggini M, Scarselli F, eds. Innovations in Neural Information – Paradigms and Applications. Studies in Computational Intelligence, 247. Berlin: Springer; 2009: 183-199
Median topographic maps for biological data sets
No full textHammer B, Hasenfuss A, Rossi F. Median topographic maps for biological data sets. In: Biehl M, Hammer B, Verleysen M, Villmann T, eds. Similarity Based Clustering. Lecture Notes Artificial Intelligence, 5400. Berlin, Heidelberg: Springer; 2009: 92-117
Militär-Marsch
No full textcomponirt und der Hamburger Garnison gewidmet von A. BiehlPreisangabe: 7 1/2 Sgr.Vorlageform des Erscheinungsvermerks: Biehl & Co Hambug. Druck von M. Dreissi
Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization
Full text linkBunte K, Hammer B, Villmann T, Biehl M, Wismüller A. Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization. In: Verleysen M, ed. ESANN'10. Proceedings of the 18th European Symposium on Artificial Neural Networks. Evere: D side; 2010: 87-92
Performance analysis of LVQ algorithms: a statistical physics approach
Full text linkGhosh A, Biehl M, Hammer B. Performance analysis of LVQ algorithms: a statistical physics approach. Neural Networks. 2006;19(6-7):817-829
Supervised dimension reduction mappings
No full textBunte K, Biehl M, Hammer B. Supervised dimension reduction mappings. In: Verleysen M, ed. European Symposium on Artificial Neural Networks. D side; 2011: pp. 281-286
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