Differential Priors for Elastic Nets


Autoria(s): Carreira-Perpinan, M.; Dayan, P.; Goodhill, G. J.
Contribuinte(s)

M. Gallagher

J. Hogan

F. Maire

Data(s)

01/01/2005

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

http://espace.library.uq.edu.au/view/UQ:102621

Idioma(s)

eng

Publicador

Springer

Palavras-Chave #E1 #239901 Biological Mathematics #780101 Mathematical sciences
Tipo

Conference Paper