Adaptive parameter selection for kernel ridge regression-Reference-Cited by-同舟云学术

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Adaptive parameter selection for kernel ridge regression

Published:2024-11 Issue: Volume:73 Page:101671
ISSN:1063-5203
Container-title:Applied and Computational Harmonic Analysis
language:en
Short-container-title:Applied and Computational Harmonic Analysis

Author:

Lin Shao-Bo

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference33 articles.

1. Optimal rates for the regularized least-squares algorithm;Caponnetto;Found. Comput. Math.,2007

2. Less is more: Nyström computational regularization;Rudi,2015

3. Divide and conquer kernel ridge regression: a distributed algorithm with minimax optimal rates;Zhang;J. Mach. Learn. Res.,2015

4. Optimal learning rates for localized svms;Meister;J. Mach. Learn. Res.,2016

5. Boosted kernel ridge regression: optimal learning rates and early stopping;Lin;J. Mach. Learn. Res.,2019

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