Nature inspiration for support vector machines

Authors:
Davide Anguita;Dario Sterpi
Affiliations:
Dept. of Biophysical and Electronic Engineering, University of Genoa, Genoa, Italy;Dept. of Biophysical and Electronic Engineering, University of Genoa, Genoa, Italy
Venue:
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Year:
2006

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Abstract

We propose in this paper a new kernel, suited for Support Vector Machines learning, which is inspired from the biological world. The kernel is based on Gabor filters that are a good model for the response of the cells in the primary visual cortex and have been shown to be very effective in processing natural images. Furthermore, we build a link between energy-efficiency, which is a driving force in biological processing systems, and good generalization ability of learning machines. This connection can be the starting point for developing new kernel-based learning algorithms.