Optimizing the data-dependent kernel under a unified kernel optimization framework

@article{Chen2008OptimizingTD,
  title={Optimizing the data-dependent kernel under a unified kernel optimization framework},
  author={Bo Chen and Hongwei Liu and Zheng Bao},
  journal={Pattern Recognition},
  year={2008},
  volume={41},
  pages={2107-2119}
}
The kernel functions play a central role in kernel methods, accordingly over the years the optimization of kernel functions has been a promising research area. Ideally Fisher discriminant criteria can be used as an objective function to optimize the kernel function to augment the margin between different classes. Unfortunately, Fisher criteria are optimal only in the case that all the classes are generated from underlying multivariate normal distributions of common covariance matrix but… CONTINUE READING

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