Risk consistency of cross-validation with Lasso-type procedures

DOI10.5705/ss.202015.0355zbMath1372.62022arXiv1308.0810OpenAlexW2963778672MaRDI QIDQ5278092

Darren Homrighausen, Daniel J. McDonald

Publication date: 13 July 2017

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1308.0810

zbMATH Keywords

regularizationmodel selectionpersistencecross-validationrisk consistencylinear oracleLasso-type procedures

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Asymptotic properties of nonparametric inference (62G20)

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On cross-validated Lasso in high dimensions ⋮ Aggregated hold out for sparse linear regression with a robust loss function ⋮ Time-varying forecast combination for high-dimensional data ⋮ A Tuning-free Robust and Efficient Approach to High-dimensional Regression ⋮ Cross-Validation With Confidence ⋮ A study on tuning parameter selection for the high-dimensional lasso ⋮ Variable selection in convex quantile regression: \(\mathcal{L}_1\)-norm or \(\mathcal{L}_0\)-norm regularization?

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