Optimally tackling covariate shift in RKHS-based nonparametric regression

DOI10.1214/23-aos2268arXiv2205.02986MaRDI QIDQ6172197

Reese Pathak, Martin J. Wainwright, Cong Ma

Publication date: 19 July 2023

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2205.02986

zbMATH Keywords

reproducing kernel Hilbert spacesnonparametric regressiontransfer learningkernel ridge regressioncovariate shift

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Minimax procedures in statistical decision theory (62C20)

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Cites Work

• Improving predictive inference under covariate shift by weighting the log-likelihood function
• A distribution-free theory of nonparametric regression
• Randomized sketches for kernels: fast and optimal nonparametric regression
• Marginal singularity and the benefits of labels in covariate-shift
• Adaptive transfer learning
• Hanson-Wright inequality in Hilbert spaces with application to \(K\)-means clustering for non-Euclidean data
• Optimal rates for the regularized least-squares algorithm
• Transfer learning for nonparametric classification: minimax rate and adaptive classifier
• High-Dimensional Statistics
• High-Dimensional Probability

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