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Basic metric learning

Hussain, Zakria, Shawe-Taylor, John, Saunders, Craig and Pasupa, Kitsuchart (2008) Basic metric learning s.n.

Record type: Monograph (Project Report)

Abstract

This report presents a a novel Multiple Kernel Learning (MKL) algorithm for the 1-class support vector machine. The emphasis is placed on viewing the CBIR task with relevance feedback as a metric learning problem, where each image has 11 different feature extraction methods applied to it. Our method attempts at finding the most compact ball amongst the 11 different feature representations using a novel 1- and 2-norm regularisation technique for the 1-class SVM under the MKL framework. We also devise a simple way of including the set of negative examples whilst still utilising the 1-class SVM implementation.

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More information

Published date: 31 December 2008
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 268316
URI: http://eprints.soton.ac.uk/id/eprint/268316
PURE UUID: e1150c80-5330-40c9-83e4-da5c6ebdf230

Catalogue record

Date deposited: 15 Dec 2009 13:32
Last modified: 18 Jul 2017 06:55

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Contributors

Author: Zakria Hussain
Author: John Shawe-Taylor
Author: Craig Saunders
Author: Kitsuchart Pasupa

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