1. State Key Laboratory of Industrial Control Technology, Department Control Science and Engineering,Zhejiang University, Hangzhou 310027,P.R.China 2. Department of Mathematics, Zhejiang University, Hangzhou 310027, P. R. China
Abstract:
Kernel-based methods work by embedding the data into a feature space and then searching linear hypothesis among the embedding data points. The performance is mostly affected by which kernel is used. A promising way is to learn the kernel from the data automatically. A general regularized risk functional (RRF) criterion for kernel matrix learning is proposed. Compared with the RRF criterion, general RRF criterion takes into account the geometric distributions of the embedding data points. It is proven that t...