Two-stage multiple kernel learning for supervised dimensionality reduction
A novel approach for non-linear supervised dimensionality reduction is proposed. The proposed method uses kernel discriminant analysis method with new kernels. A multiple kernel learning (MKL) paradigm produces the new kernel function. Proper criteria for supervised dimensionality reduction are optimized in the MKL part. The proposed method is successfully evaluated using many real-world datasets.
multiple kernel learning supervised dimensionality reduction objection recognition handwritten digit recognition pattern recognition