Variable Sparsity Kernel Learning

@article{Aflalo2011VariableSK,
  title={Variable Sparsity Kernel Learning},
  author={Jonathan Aflalo and Aharon Ben-Tal and Chiranjib Bhattacharyya and J. Saketha Nath and Raman Sankaran},
  journal={Journal of Machine Learning Research},
  year={2011},
  volume={12},
  pages={565-592}
}
This paper 1 presents novel algorithms and applications for a particula r class of mixed-norm regularization based Multiple Kernel Learning (MKL) formulat ions. The formulations assume that the given kernels are grouped and employ l1 norm regularization for promoting sparsity within RKHS norms of each group and ls,s≥ 2 norm regularization for promoting non-sparse combinations across groups. Various sparsity levels in combining t he kernels can be achieved by varying the grouping of kernels… CONTINUE READING
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