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Distributing SOM ensemble training using grid middleware

Vrusias, BL, Vomvoridis, L and Gillam, L (2007) Distributing SOM ensemble training using grid middleware IEEE International Joint Conference on Neural Networks (IJCNN 2007). pp. 2712-2717.

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In this paper we explore the distribution of training of self-organised maps (SOM) on grid middleware. We propose a two-level architecture and discuss an experimental methodology comprising ensembles of SOMs distributed over a grid with periodic averaging of weights. The purpose of the experiments is to begin to systematically assess the potential for reducing the overall time taken for training by a distributed training regime against the impact on precision. Several issues are considered: (i) the optimum number of ensembles; (ii) the impact of different types of training data; and (iii) the appropriate period of averaging. The proposed architecture has been evaluated in a grid environment, with clock-time performance recorded.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Computer Science
Authors : Vrusias, BL, Vomvoridis, L and Gillam, L
Date : 2007
DOI : 10.1109/IJCNN.2007.4371387
Additional Information :

Copyright 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

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Date Deposited : 16 Nov 2012 10:10
Last Modified : 06 Jul 2019 05:11

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