Refereed full papers (journals, book chapters, international conferences)

1994

@article{LLM1994,
	vgclass =	{refpap},
	vgproject =	{nn},
	author =	{Asriel U. Levin, Todd K. Leen and John E. Moody},
	title =	{Fast Pruning Using Principal Components},
	journal =	{Advances in Neural Information Processing Systems},
	volume =	{6},
	pages =	{35--42},
	year =	{1994},
	abstract =	{We present a new algorithm for eliminating excess
	parameters and improving network generalization after supervised
	training. The method. ``Principal Components Pruning (PCP)'', is based
	on principal components analysis of the node activations of successive
	layers of the network. It is simple, cheap to implement, and effective.
	It requires no network retraining, and does not involve calculating the
	full Hessian of the cost function. Only the weight and node activity
	correlation matrices for each layer of nodes are required. We
	demonstrate the efficacy of the method on a regression problem using
	polynomial basis functions, and on an economic time series prediction
	problem using a two-layer, feedforward network.},
}