Rosen’s projection method for SVM training

This is an electronic version of the paper presented at the 17th European Symposium on Artificial Neural Networks, held in Bruges on 2009In this work we will give explicit formulae for the application of Rosen’s gradient projection method to SVM training that leads to a very simple implementation. We shall experimentally show that the method provides good descent directions that result in less training iterations, particularly when large precision is wanted. However, a naive kernelization may end up in a procedure requiring more KOs than SMO and further work is needed to arrive at an efficient implementation.With partial support of Spain’s TIN 2007–66862 project and Cátedra UAM–IIC en Modelado y Predicción. The first author is kindly supported by FPU-MICINN grant reference AP2007–00142