PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Speeding up the IRWLS convergence to the SVM solution
Fernando Perez-Cruz and Antonio Artes-Rodriguez
In: International Joint Conference on Neural Networks, July 2004, Budapest.

Abstract

We present the convergence demonstration of the Iterative Re-Weighted Least Squares (IRWLS) procedure to the SVM solution, to propose two modifications, which significantly reduces the runtime complexity of the IRWLS. We show by means of computer experiments that the convergence can be speed up between two and eight times compare to the standard IRWLS procedure.

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EPrint Type:Conference or Workshop Item (Invited Talk)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:530
Deposited By:Fernando Perez-Cruz
Deposited On:24 December 2004