We consider learning on multi-layer neural nets with piecewise polynomial
activation functions and a fixed number k of numerical inputs. We exhibit
arbitrarily large network architectures for which efficient and provably
successful learning algorithms exist in the rather realistic refinement of
Valiant's model for probably approximately correct learning ("PAC-learning")
where ... more >>>