2022
DOI: 10.21203/rs.3.rs-2176587/v1
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Sketching the Krylov Subspace: Faster Computation of the Entire Ridge Regularization Path

Abstract: We propose a fast algorithm for computing the entire ridge regression regularization path in nearly linear time. Our method constructs a basis on which the solution of ridge regression can be computed instantly for any value of the regularization parameter. Consequently, linear models can be tuned via cross-validation or other risk estimation strategies with substantially better efficiency. The algorithm is based on iteratively sketching the Krylov subspace with a binomial decomposition over the regularization… Show more

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