The New ERA in Supervised Learning.
Conventional methods of supervised learning are inevitably faced with the problem of local minima; evidence is presented that second order methods such as the conjugate gradient and quasi-Newton techniques are particularly susceptible to being trapped in sub-optimal solutions. A new technique, expanded range approximation (ERA), is presented, which by the use of a homotopy on the range of the target outputs allows supervised learning methods to find a global minimum of the error function in almost every case. Copyright 1997 Elsevier Science Ltd. All Rights Reserved.
TAYLOR
JOHN G.
JG
King's College, London, UK
SHEPHERD
ADRIAN J.
AJ
GORSE
DENISE
D