In this paper, we model large support vector machines (SVMs) by smaller networks in order to decrease the computational cost. The key idea is to generate additional training patterns using a trained SVM and use these additional patterns along with the original training patterns to train a neural network. Results verify the validity of the technique.
Pramod Lakshmi Narasimha, Sanjeev S. Malalur, Mich