Pages that link to "Item:Q2835989"
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The following pages link to Error bounds for learning the kernel (Q2835989):
Displaying 21 items.
- Error bounds for \(l^p\)-norm multiple kernel learning with least square loss (Q448851) (← links)
- Learning with generalization capability by kernel methods of bounded complexity (Q558012) (← links)
- Learning and approximation by Gaussians on Riemannian manifolds (Q960002) (← links)
- Kernel selection with spectral perturbation stability of kernel matrix (Q1616171) (← links)
- Fast learning rate of non-sparse multiple kernel learning and optimal regularization strategies (Q1657947) (← links)
- Optimal regression rates for SVMs using Gaussian kernels (Q1951100) (← links)
- Reproducing kernels and choices of associated feature spaces, in the form of \(L^2\)-spaces (Q2235966) (← links)
- Asymptotic analysis of the learning curve for Gaussian process regression (Q2339938) (← links)
- Feature space perspectives for learning the kernel (Q2384133) (← links)
- Learning with sample dependent hypothesis spaces (Q2389476) (← links)
- Deterministic error bounds for kernel-based learning techniques under bounded noise (Q2665700) (← links)
- Error bounds for learning the kernel (Q2835989) (← links)
- Bias corrected regularization kernel method in ranking (Q4615656) (← links)
- (Q4645667) (← links)
- (Q4783902) (← links)
- Positive Semi-definite Embedding for Dimensionality Reduction and Out-of-Sample Extensions (Q5065468) (← links)
- Generalized support vector regression: Duality and tensor-kernel representation (Q5220070) (← links)
- Learning rates for partially linear support vector machine in high dimensions (Q5856267) (← links)
- Conditional mean embedding and optimal feature selection via positive definite kernels (Q6091085) (← links)
- Optimality of regularized least squares ranking with imperfect kernels (Q6125450) (← links)
- Analysis of regularized least squares ranking with centered reproducing kernel (Q6591691) (← links)
