Gorse, D; Shepherd, AJ; Taylor, JG; (1997) The new ERA in supervised learning. NEURAL NETWORKS , 10 (2) 343 - 352.
Full text not available from this repository.
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. (C) 1997 Elsevier Science Ltd All Rights Reserved.
|Title:||The new ERA in supervised learning|
|Keywords:||global optimisation, local minima, homotopy, range expansion, TUNNELING ALGORITHM, LOCAL MINIMA, OPTIMIZATION, PROPAGATION, PERCEPTRONS|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science > Computer Science|
Archive Staff Only: edit this record