Learning rates of regularized regression on the unit sphere

Author:

Cao FeiLong,Lin ShaoBo,Chang XiangYu,Xu ZongBen

Publisher

Springer Science and Business Media LLC

Subject

General Mathematics

Reference25 articles.

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2. Belkin M, Niyogi P, Sindwani V. Manifold regularization: A geometric framework for learning from examples. Computer Science Technical Report of University of Chicago (TR-2004-06), 2004

3. Belkin M, Niyogi P. Semi-supervised learning on Riemannian manifolds. Machine Learning, 2004, 56: 209–239

4. Chen D R, Wu Q, Ying Y M, et al. Support vector machine soft margin classifiers: Error analysis. J Mach Learning Res, 2004, 5: 1143–1175

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1. Reproducing property of bounded linear operators and kernel regularized least square regressions;International Journal of Wavelets, Multiresolution and Information Processing;2024-04-22

2. Complexity of Monte Carlo integration for Besov classes on the unit sphere;Annals of Functional Analysis;2022-12-19

3. The kernel regularized learning algorithm for solving Laplace equation with Dirichlet boundary;International Journal of Wavelets, Multiresolution and Information Processing;2022-09-05

4. Nonparametric regression using needlet kernels for spherical data;Journal of Complexity;2019-02

5. Nonparametric Regression for Spherical Data;Journal of the American Statistical Association;2014-04-03

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