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ℓ 1 -regularised linear regression: persistence and oracle inequalities

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Bartlett, Peter
Mendelson, Shahar
Neeman, Joseph

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Springer

Abstract

We study the predictive performance of ℓ1-regularized linear regression in a model-free setting, including the case where the number of covariates is substantially larger than the sample size. We introduce a new analysis method that avoids the boundedne

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Probability Theory and Related Fields

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Restricted until

2037-12-31