Signal Theory for SVM Kernel Parameter Estimation

@article{Nelson2006SignalTF,
  title={Signal Theory for SVM Kernel Parameter Estimation},
  author={J. Nelson and R. I. Damper and S. Gunn and Baofeng Guo},
  journal={2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing},
  year={2006},
  pages={149-154}
}
Fourier-based regularisation is considered for the support vector machine classification problem over absolutely integrable loss functions. By invoking the modest assumption that the decision function belongs to a Paley-Wiener space, it is shown that the classification problem can be developed in the context of signal theory. Furthermore, by employing the… CONTINUE READING