Pages that link to "Item:Q974504"
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The following pages link to Learning rates of multi-kernel regularized regression (Q974504):
Displaying 17 items.
- Fast learning rate of multiple kernel learning: trade-off between sparsity and smoothness (Q366980) (← links)
- Error bounds for \(l^p\)-norm multiple kernel learning with least square loss (Q448851) (← links)
- Optimal learning rates of \(l^p\)-type multiple kernel learning under general conditions (Q526680) (← links)
- Learning rates for multi-kernel linear programming classifiers (Q537615) (← links)
- Statistical analysis of the moving least-squares method with unbounded sampling (Q726158) (← links)
- Multi-kernel regularized classifiers (Q870343) (← links)
- Optimal learning rates for kernel partial least squares (Q1645280) (← links)
- Approximation analysis of gradient descent algorithm for bipartite ranking (Q1760585) (← links)
- Learning rates of multi-kernel regression by orthogonal greedy algorithm (Q1926541) (← links)
- Learning rates for the kernel regularized regression with a differentiable strongly convex loss (Q2191832) (← links)
- Reproducing kernels and choices of associated feature spaces, in the form of \(L^2\)-spaces (Q2235966) (← links)
- Learning performance of regularized regression with multiscale kernels based on Markov observations (Q2244161) (← links)
- Optimal convergence rates of high order Parzen windows with unbounded sampling (Q2251679) (← links)
- Improvement of multiple kernel learning using adaptively weighted regularization (Q3121201) (← links)
- Learning Rates of <i>l<sup>q</sup></i> Coefficient Regularization Learning with Gaussian Kernel (Q5175497) (← links)
- Randomized multi-scale kernels learning with sparsity constraint regularization for regression (Q5204655) (← links)
- Refined Rademacher Chaos Complexity Bounds with Applications to the Multikernel Learning Problem (Q5378343) (← links)
