This is now an inactive research group it's members have moved on. You can find them at their new research groups:
Research Projects

Research Projects

Development and Application of String Type Kernels
(this project has ended)

Classes of kernels which operate on discrete structures have been proposed relatively recently which allow the successful family of kernel-based algorithms to work directly on strings, trees, and other objects without the need to first convert them into an explicit vector representation first. It has been shown that there is a probablistic interpretation of the string kernel, which strongly relates string kernels and fisher kernels. This has lead to a kernel over a finite state automata which deals with variable-length substrings. This project intends to extend the work in this area by examining the area of kernels from generative models, with applications to text-categorisation, bioinformatics tasks and image classification. The project will also consider clustering algorithms using domain-specific kernels.

Type: Normal Research Project
Research Group: Information: Signals, Images, Systems Research Group
Theme: Machine Learning
Dates: 1st Febuary 2004 to 31st January 2006

Funding

  • EPSRC

Principal Investigators

  • cjs

Other Investigators

  • av

Associated Publications

Welcome to ePrints Soton - ePrints Soton
The University of Southampton

Welcome to ePrints Soton

Welcome to the University of Southampton Institutional Research Repository, ePrints Soton. This repository contains details and, if available, downloads of our research output.

Information on this website should be updated via PURE, our research management system. For issues and queries on outputs and open access, please contact the ePrints team at eprints@soton.ac.uk or view the University's Pure support pages.

Search Repository

Search the repository using a full range of fields. Use the search field at the top of the page for a quick search.

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://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.

×
© School of Electronics and Computer Science of the University of Southampton