Sets of multivariable functions that can be approximated with “dimension-independent” rates either by linear approximators or by neural networks having various types of computational units are compared. The comparison is made by exhibiting families of functions belonging to suitable difference sets
On Dimension-Independent Approximation by Neural Networks and Linear Approximators
GIULINI, SAVERIO;SANGUINETI, MARCELLO
2000-01-01
Abstract
Sets of multivariable functions that can be approximated with “dimension-independent” rates either by linear approximators or by neural networks having various types of computational units are compared. The comparison is made by exhibiting families of functions belonging to suitable difference setsFile in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.