@inproceedings{2018,
  title = {Kernel Methods and Their Applications to Signal Processing},
  journal = {IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP ‘03)},
  booktitle = {Proceedings. (ICASSP ‘03)},
  abstract = {Recently introduced in Machine Learning, the notion of kernels has
  drawn a lot of interest as it allows to obtain non-linear algorithms
  from linear ones in a simple and elegant manner. This, in conjunction
  with the introduction of new linear classification methods such as the
  Support Vector Machines has produced significant progress. The
  successes of such algorithms is now spreading as they are applied to
  more and more domains. Many Signal Processing problems, by their
  non-linear and high-dimensional nature may benefit from such
  techniques. We give an overview of kernel methods and their recent
  applications.},
  volume = {Special Session on Kernel Methods},
  pages = {860 },
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  year = {2003},
  author = {Bousquet, O. and Perez-Cruz, F.}
}