@article{5776,
  title = {Constructing Sparse Kernel Machines Using Attractors},
  journal = {IEEE Transactions on Neural Networks},
  abstract = {In this brief, a novel method that constructs a sparse kernel machine is proposed. The proposed method generates attractors as sparse solutions from a built-in kernel machine via a dynamical system framework. By readjusting the corresponding coefficients and bias terms, a sparse kernel machine that approximates a conventional kernel machine is constructed. The simulation results show that the constructed sparse kernel machine improves the efficiency of testing phase while maintaining comparable test error.},
  volume = {20},
  number = {4},
  pages = {721-729},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = apr,
  year = {2009},
  slug = {5776},
  author = {Lee, D. and Jung, K-H. and Lee, J.},
  month_numeric = {4}
}