PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A New Scatter-Based Multi-Class Support Vector Machine
Robert Jenssen, Marius Kloft, Sören Sonnenburg, Alexander Zien and Klaus-Robert Müller
In: Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing (2011) IEEE , Beijing, China , pp. 1-6. ISBN 1551-2541

Abstract

We provide a novel interpretation of the dual of support vector machines (SVMs) in terms of scatter with respect to class prototypes and their mean. As a key contribution, we extend this framework to multiple classes, providing a new joint Scatter SVM algorithm, at the level of its binary counterpart in the number of optimization variables. We identify the associated primal problem and develop a fast chunking-based optimizer. Promising results are reported, also compared to the state-of-the-art, at lower computational complexity.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:9434
Deposited By:Marius Kloft
Deposited On:16 March 2012