MLP in layer-wise form with applications to weight decay.
A simple and general calculus for the sensitivity analysis of a feedforward MLP network in a layer-wise form is presented. Based on the local optimality conditions, some consequences for the least-means-squares learning problem are stated and further discussed. Numerical experiments with formulation and comparison of different weight decay techniques are included.
Kärkkäinen
Tommi
T
Department of Mathematical Information Technology, University of Jyväskylä, P.O.Box 35 (Agora), FIN-40351 Jyväskylä, Finland. tka@mit.jyu.fi