Functional Optimisation of Online Algorithms in Multilayer Neural Networks

Details Functional Optimisation of Online Algorithms in Multilayer Neural Networks Functional Optimisation of Online Algorithms in Multilayer Neural Networks

1997-06-02

arxiv.org/abs/cond-mat/9706015v1

J. Phys A: Math. Gen. 30 (1997) L599-L605

Physics

Condensed Matter

Disordered Systems and Neural Networks

Scientific paper

10.1088/0305-4470/30/17/002

We study the online dynamics of learning in fully connected soft committee machines in the student-teacher scenario. The locally optimal modulation function, which determines the learning algorithm, is obtained from a variational argument in such a manner as to maximise the average generalisation error decay per example. Simulations results for the resulting algorithm are presented for a few cases. The symmetric phase plateaux are found to be vastly reduced in comparison to those found when online backpropagation algorithms are used. A discussion of the implementation of these ideas as practical algorithms is given.

Affiliated with

Also associated with

No associations

Rating

Functional Optimisation of Online Algorithms in Multilayer Neural Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Functional Optimisation of Online Algorithms in Multilayer Neural Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Functional Optimisation of Online Algorithms in Multilayer Neural Networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-117042