Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. For technical support, please contact us at onlinesupport@ieee.org. We apologize for any inconvenience.
By Topic

Load sharing in the training set partition algorithm for parallel neural learning

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Girau, B. ; Lab. d''Inf. du Parallelisme, CNRS, Lyon, France ; Paugam-Moisy, H.

A parallel back-propagation algorithm that partitions the training set on a ring of processors has been introduced. In this paper, we study the performance of this algorithm on MIMD machines and develop a new version, based on a heterogeneous load sharing. Algebraic models allow precise comparisons between the different methods, and show great improvements in case of parallel learning

Published in:

Parallel Processing Symposium, 1995. Proceedings., 9th International

Date of Conference:

25-28 Apr 1995