Differential Priors for Elastic Nets
Contribuinte(s) |
M. Gallagher J. Hogan F. Maire |
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Data(s) |
01/01/2005
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Resumo |
The elastic net and related algorithms, such as generative topographic mapping, are key methods for discretized dimension-reduction problems. At their heart are priors that specify the expected topological and geometric properties of the maps. However, up to now, only a very small subset of possible priors has been considered. Here we study a much more general family originating from discrete, high-order derivative operators. We show theoretically that the form of the discrete approximation to the derivative used has a crucial influence on the resulting map. Using a new and more powerful iterative elastic net algorithm, we confirm these results empirically, and illustrate how different priors affect the form of simulated ocular dominance columns. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Springer |
Palavras-Chave | #E1 #239901 Biological Mathematics #780101 Mathematical sciences |
Tipo |
Conference Paper |