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Empirical Effective Dimension and Optimal Rates for Regularized Least Squares Algorithm
This paper presents an approach to model selection for regularized least-squares on reproducing kernel Hilbert spaces in the semi-supervised setting. The role of effective dimension was recently shown to be crucial in the ...
Fast Rates for Regularized Least-squares Algorithm
We develop a theoretical analysis of generalization performances of regularized least-squares on reproducing kernel Hilbert spaces for supervised learning. We show that the concept of effective dimension of an integral ...
Risk Bounds for Regularized Least-squares Algorithm with Operator-valued kernels
We show that recent results in  on risk bounds for regularized least-squares on reproducing kernel Hilbert spaces can be straightforwardly extended to the vector-valued regression setting. We first briefly introduce ...