The University of Southampton
University of Southampton Institutional Repository

Generalisation Error Bound for Sparse Linear Classifiers

Generalisation Error Bound for Sparse Linear Classifiers
Generalisation Error Bound for Sparse Linear Classifiers
1-55860-703-X
298-303
Morgan Kaufmann
Graepel, Thore
f01fa538-c0f8-4e36-bbcc-698366e73f39
Herbrich, Ralf
3024ba7e-f3a1-4187-8655-b7f163c7c733
Shawe-Taylor, John
b1931d97-fdd0-4bc1-89bc-ec01648e928b
Graepel, Thore
f01fa538-c0f8-4e36-bbcc-698366e73f39
Herbrich, Ralf
3024ba7e-f3a1-4187-8655-b7f163c7c733
Shawe-Taylor, John
b1931d97-fdd0-4bc1-89bc-ec01648e928b

Graepel, Thore, Herbrich, Ralf and Shawe-Taylor, John (2000) Generalisation Error Bound for Sparse Linear Classifiers. In Proceedings of Computational Learning Theory Conference, COLT'2K. Morgan Kaufmann. pp. 298-303 .

Record type: Conference or Workshop Item (Paper)

Full text not available from this repository.

More information

Published date: 2000
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 259640
URI: http://eprints.soton.ac.uk/id/eprint/259640
ISBN: 1-55860-703-X
PURE UUID: 5a6071d0-0bf4-4946-a2b5-be28cda22c26

Catalogue record

Date deposited: 03 Aug 2004
Last modified: 18 Jul 2017 09:20

Export record

Contributors

Author: Thore Graepel
Author: Ralf Herbrich
Author: John Shawe-Taylor

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×