Canonical correlation analysis; An overview with application to learning methods
Hardoon, David R., Szedmak, Sandor and Shawe-Taylor, John (2003) Canonical correlation analysis; An overview with application to learning methods.
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Description/Abstract
We present a general method using kernel Canonical Correlation Analysis to learn a semantic representation to web images and their associated text. The semantic space provides a common representation and enables a comparison between the text and images. In the experiments we look at two approaches of retrieving images based only on their content from a text query. We compare the approaches against a standard cross-representation retrieval technique known as the Generalised Vector Space Model.
| Item Type: | Monograph (Technical Report) |
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| Related URLs: | |
| Keywords: | Canonical correlation analysis, kernel canonical correlation analysis, partial Gram-Schmidt orthogonolisation, Cholesky decomposition, incomplete Cholesky decomposition, kernel methods. |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science |
| Item ID: | 259225 |
| Date Deposited: | 24 Mar 2004 |
| Last Modified: | 02 Mar 2012 02:33 |
| Contributors: | Hardoon, David R. (Author) Szedmak, Sandor (Author) Shawe-Taylor, John (Author) |
| Date: | May 2003 |
| Status: | Published |
| Further Information: | Google Scholar |
| URI: | http://eprints.soton.ac.uk/id/eprint/259225 |
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