Multiple Kernel Learning with Gaussianity Measures

  title={Multiple Kernel Learning with Gaussianity Measures},
  author={Hideitsu Hino and Nima Reyhani and Noboru Murata},
  journal={Neural Computation},
Kernel methods are known to be effective for nonlinear multivariate analysis. One of the main issues in the practical use of kernel methods is the selection of kernel. There have been a lot of studies on kernel selection and kernel learning. Multiple kernel learning (MKL) is one of the promising kernel optimization approaches. Kernel methods are applied to various classifiers including Fisher discriminant analysis (FDA). FDA gives the Bayes optimal classification axis if the data distribution… CONTINUE READING
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