The University of Southampton
University of Southampton Institutional Repository

Constant Rate Approximate Maximum Margin Algorithms

Tsampouka, Petroula and Shawe-Taylor, John (2006) Constant Rate Approximate Maximum Margin Algorithms s.n.

Record type: Monograph (Project Report)


We present a new class of perceptron-like algorithms with margin in which the “effective” learning rate, defined as the ratio of the learning rate to the length of the weight vector, remains constant. We prove that the new algorithms converge in a finite number of steps and show that there exists a limit of the parameters involved in which convergence leads to classification with maximum margin.

PDF constant_rate.pdf - Other
Download (221kB)

More information

Published date: 2006
Keywords: online learning, maximum margin classifiers
Organisations: Electronics & Computer Science


Local EPrints ID: 261832
PURE UUID: c021d6af-2445-4046-b41b-c300429a220d

Catalogue record

Date deposited: 26 Jan 2006
Last modified: 18 Jul 2017 08:58

Export record


Author: Petroula Tsampouka
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 supports OAI 2.0 with a base URL of

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.