title: The New ERA in Supervised Learning.
abstract: 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.
authors.affiliation: King's College, London, UK
authors.forename: JOHN G.
authors.initials: JG
authors.lastname: TAYLOR
authors.forename: ADRIAN J.
authors.initials: AJ
authors.lastname: SHEPHERD
authors.forename: DENISE
authors.initials: D
authors.lastname: GORSE