An elementary analysis of ridge regression with random design
arXiv:2203.08564v219 citationsh-index: 53
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This is an incremental theoretical contribution for researchers in statistical learning, offering a simplified analysis of a well-known method.
The authors tackled the problem of analyzing the prediction error of ridge regression with random design, providing a short and self-contained proof that bypasses the use of Rudelson's deviation inequality.
In this note, we provide an elementary analysis of the prediction error of ridge regression with random design. The proof is short and self-contained. In particular, it bypasses the use of Rudelson's deviation inequality for covariance matrices, through a combination of exchangeability arguments, matrix perturbation and operator convexity.