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

1993

@article{Sha1993,
	vgclass =	{refpap},
	vgproject =	{nn,invariance},
	author =	{John Shawe-Taylor},
	title =	{Symmetries and Discriminability in Feedforward Network
	Architectures},
	journal =	{IEEE Transactions on Neural Networks},
	volume =	{4},
	number =	{5},
	pages =	{816--826},
	month =	{September},
	year =	{1993},
	abstract =	{This paper investigates the effects of introducing
	symmetries into feedforward neural networks in what are termed symmetry
	networks. This technique allows more efficient training for problems in
	which we require the output of a network to be invariant under a set of
	transformations of the input. The particular problem of graph
	recognition is considered. In this case the network is designed to
	deliver the same output for isomorphic graphs. This leads to the
	question of which inputs can be distinguished by such architectures. A
	theorem characterising when two inputs can be distinguished by a
	symmetry network is given. As a consequence, a particular network
	design is shown to be able to distinguish nonisomorphic graphs if and
	only if the graph reconstruction conjecture holds.},
}