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Why is computing ridge regression with a Cholesky decomposition much quicker than using SVD?
First, we note that ridge regression can be transformed into an OLS problem via the data augmentation trick.. This adds $p$ rows to the design matrix $\mathbf{X}$, so the new matrix $\mathbf{X}_\lambd …