Pages that link to "Item:Q882223"
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The following pages link to Learning the kernel matrix by maximizing a KFD-based class separability criterion (Q882223):
Displaying 14 items.
- A novel kernel-based maximum a posteriori classification method (Q280412) (← links)
- Learning with infinitely many features (Q374174) (← links)
- Scaling the kernel function based on the separating boundary in input space: a data-dependent way for improving the performance of kernel methods (Q425515) (← links)
- Kernel self-optimization learning for kernel-based feature extraction and recognition (Q498017) (← links)
- Evolutionary combination of kernels for nonlinear feature transformation (Q726372) (← links)
- Ideal regularization for learning kernels from labels (Q889267) (← links)
- An efficient kernel matrix evaluation measure (Q941581) (← links)
- Learning the optimal kernel for Fisher discriminant analysis via second order cone programming (Q1046076) (← links)
- Multiple kernel clustering based on centered kernel alignment (Q1676950) (← links)
- Gaussian bandwidth selection for manifold learning and classification (Q2212526) (← links)
- A kernel optimization method based on the localized kernel Fisher criterion (Q2462603) (← links)
- Optimizing the data-dependent kernel under a unified kernel optimization framework (Q2476978) (← links)
- Learning the kernel parameters in kernel minimum distance classifier (Q2573639) (← links)
- (Q3169473) (← links)
