An Accelerated MDM Algorithm for SVM Training
Álvaro Barbero Jiménez, Jorge López Lázaro, José R. Dorronsoro · The European Symposium on Artificial Neural Networks · 2008
In this work we will propose an acceleration procedure for the Mitchell{Demyanov{Malozemov (MDM) algorithm (a fast geometric algo- rithm for SVM construction) that may yield quite large training savings. While decomposition algorithms such as SVMLight or SMO are usually the SVM methods of choice, we shall show that there is a relationship between SMO and MDM that suggests that, at least in their simplest implemen- tations, they should have similar training speeds. Thus, and although we will not discuss it here, the proposed MDM acceleration might be used as a starting point to new ways of accelerating SMO.