L2-SVM training with distributed data

Authors:
Stefano Lodi;Ricardo Ñanculef;Claudio Sartori
Affiliations:
Dept. of Electronics, Comp. Sc. and Systems, University of Bologna, Italy;Department of Informatics, Federico Santa María University, Chile;Dept. of Electronics, Comp. Sc. and Systems, University of Bologna, Italy
Venue:
MATES'09 Proceedings of the 7th German conference on Multiagent system technologies
Year:
2009

Citing 4
Cited 0

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Abstract

We propose an algorithm for the problem of training a SVM model when the set of training examples is horizontally distributed across several data sources. The algorithm requires only one pass through each remote source of training examples, and its accuracy and efficiency follow a clear pattern as function of a user-defined parameter. We outline an agent-based implementation of the algorithm.