Asymptotic Bias and Variance of Kernel Ridge Regression

Victor Solo

ICASSP 2023accepted0 citations

Asymptotic Bias and Variance of Kernel Ridge Regression

Abstract

Kernel ridge regression is widely used but the theory of its performance has never been fully developed. While there are results on convergence there are few on bias and variance. Here we find expressions for local bias and variance for the important case of the exponential quadratic kernel. Using these new expressions, we explain when quadratic exponential kernel ridge regression can work well and when it will fail.

BibTeX

@inproceedings{icassp2023_asymptoticbiasan,
  title = {Asymptotic Bias and Variance of Kernel Ridge Regression},
  author = {Victor Solo},
  booktitle = {ICASSP 2023},
  year = {2023}
}