Input Pruning for Neural Gas Architectures

Hammer B, Villmann T (2001)
In: Proc. Of European Symposium on Artificial Neural Networks (ESANN'2001). Brussels, Belgium: D facto publications: 283-288.

Konferenzbeitrag | Veröffentlicht | Englisch
 
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Autor*in
Hammer, BarbaraUniBi ; Villmann, Th.
Erscheinungsjahr
2001
Titel des Konferenzbandes
Proc. Of European Symposium on Artificial Neural Networks (ESANN'2001)
Seite(n)
283-288
Konferenz
ESANN'2001
Page URI
https://pub.uni-bielefeld.de/record/1993768

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Hammer B, Villmann T. Input Pruning for Neural Gas Architectures. In: Proc. Of European Symposium on Artificial Neural Networks (ESANN'2001). Brussels, Belgium: D facto publications; 2001: 283-288.
Hammer, B., & Villmann, T. (2001). Input Pruning for Neural Gas Architectures. Proc. Of European Symposium on Artificial Neural Networks (ESANN'2001), 283-288. Brussels, Belgium: D facto publications.
Hammer, Barbara, and Villmann, Th. 2001. “Input Pruning for Neural Gas Architectures”. In Proc. Of European Symposium on Artificial Neural Networks (ESANN'2001), 283-288. Brussels, Belgium: D facto publications.
Hammer, B., and Villmann, T. (2001). “Input Pruning for Neural Gas Architectures” in Proc. Of European Symposium on Artificial Neural Networks (ESANN'2001) (Brussels, Belgium: D facto publications), 283-288.
Hammer, B., & Villmann, T., 2001. Input Pruning for Neural Gas Architectures. In Proc. Of European Symposium on Artificial Neural Networks (ESANN'2001). Brussels, Belgium: D facto publications, pp. 283-288.
B. Hammer and T. Villmann, “Input Pruning for Neural Gas Architectures”, Proc. Of European Symposium on Artificial Neural Networks (ESANN'2001), Brussels, Belgium: D facto publications, 2001, pp.283-288.
Hammer, B., Villmann, T.: Input Pruning for Neural Gas Architectures. Proc. Of European Symposium on Artificial Neural Networks (ESANN'2001). p. 283-288. D facto publications, Brussels, Belgium (2001).
Hammer, Barbara, and Villmann, Th. “Input Pruning for Neural Gas Architectures”. Proc. Of European Symposium on Artificial Neural Networks (ESANN'2001). Brussels, Belgium: D facto publications, 2001. 283-288.
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