General Riemannian SOM

Kohonen's Self-Organizing Maps (SOMs) have proven to be a successful data-reduction method to identify the intrinsic lower-dimensional sub-manifold of a data set that is scattered in the higher-dimensional feature space. Motivated by the possibly non-Euclidian nature of the feature space and of...

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Bibliographische Detailangaben

1. Verfasser:	Schewtschenko, Jascha A
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Neural and Evolutionary Computing
Online-Zugang:	Volltext bestellen
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