Spectrally-truncated kernel ridge regression and its free lunch

DOI10.1214/21-EJS1873zbMath1471.62320arXiv1906.06276OpenAlexW3186080338MaRDI QIDQ2233553

Arash A. Amini

Publication date: 11 October 2021

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1906.06276

zbMATH Keywords

ridge regressionkernel methodsspectral truncationnonparametric regressionminimax estimation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Minimax procedures in statistical decision theory (62C20)

Cites Work

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• Estimating the Largest Eigenvalue by the Power and Lanczos Algorithms with a Random Start
• High-Dimensional Statistics
• Improved Bounds for the Nyström Method With Application to Kernel Classification
• All of Nonparametric Statistics
• Introduction to nonparametric estimation

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