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A Randomized Algorithm for Large Scale Support Vector Learning

Krishnan, S and Bhattacharyya, Chiranjib and Hariharan, Ramesh and Genomics, Strand (2007) A Randomized Algorithm for Large Scale Support Vector Learning. In: Proceedings of 21st Annual Conference on Neural Information Processing Systems (NIPS), June 2007.

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Abstract

We propose a randomized algorithm for large scale SVM learning which solves the problem by iterating over random subsets of the data. Crucial to the algorithm for scalability is the size of the subsets chosen. In the context of text classification we show that, by using ideas from random projections, a sample size of O(log n) can be used to obtain a solution which is close to the optimal with a high probability. Experiments done on synthetic and real life data sets demonstrate that the algorithm scales up SVM learners, without loss in accuracy. 1

Item Type: Conference Paper
Department/Centre: Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)
Date Deposited: 17 Oct 2011 05:10
Last Modified: 17 Oct 2011 05:10
URI: http://eprints.iisc.ernet.in/id/eprint/41464

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