%A Giorgio Gnecco
%A Marcello Sanguineti
%D 2009
%L eprints1708
%K Learning from data; Regularization; Weight decay; Suboptimal solutions; Rates of convergence
%X The technique known as ?weight decay? in the literature about learning from data is investigated using tools from regularization theory. Weight-decay regularization is compared with Tikhonov?s regularization of the learning problem and with a mixed regularized learning technique. The accuracies of suboptimal solutions to weight-decay learning are estimated for connectionistic models with a-priori fixed numbers of computational units.
%I Springer
%N 1
%V 6
%P 53-79
%J Computational Management Science
%R 10.1007/s10287-008-0072-5
%T The weight-decay technique in learning from data: an optimization point of view