shift invariance

[John Donald]

Abu-Mostafa's "learning from hints" is a very simple approach to learning
neural net representations of functions that satisfy global constraints
such as shift invariance. Cf Scientific American April 1995 (!) and the
references therein, eg. "Learning from hints", Yaser Abu-Mostafa,
J. of Complexity 10 (165-178), 1994.

His idea is to add to the training examples additional invented examples
that represent the global properties. He claims significant speed-up, eg
in training nets to learn an even (global property) shift invariant
(global) function.