Estimating the moments of a random vector with applications
Shawe-Taylor, John and Cristianini, Nello (2003) Estimating the moments of a random vector with applications. In, Proceedings of GRETSI 2003 Conference. , , 47-52.
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Description/Abstract
A general result about the quality of approximation of the mean of a distribution by its empirical estimate is proven that does not involve the dimension of the feature space. Using the kernel trick this gives also bounds the quality of approximation of higher order moments. A number of applications are derived of interest in learning theory including a new novelty detection algorithm and rigorous bounds on the Robust Minimax Classification algorithm.
| Item Type: | Book Section |
|---|---|
| Additional Information: | Invited Talk |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science |
| Item ID: | 260372 |
| Date Deposited: | 26 Jan 2005 |
| Last Modified: | 02 Mar 2012 01:34 |
| Contributors: | Shawe-Taylor, John (Author) Cristianini, Nello (Author) |
| Date: | 2003 |
| Additional Information: | Invited Talk |
| Status: | Published |
| Further Information: | Google Scholar |
| URI: | http://eprints.soton.ac.uk/id/eprint/260372 |
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