The distribution of the Lasso: uniform control over sparse balls and adaptive parameter tuning
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Publication:2054498
DOI10.1214/20-AOS2038zbMath1480.62145arXiv1811.01212OpenAlexW3202433451MaRDI QIDQ2054498
Publication date: 3 December 2021
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1811.01212
Related Items (13)
Fundamental barriers to high-dimensional regression with convex penalties ⋮ Surprises in high-dimensional ridgeless least squares interpolation ⋮ Aggregated hold out for sparse linear regression with a robust loss function ⋮ Sharp global convergence guarantees for iterative nonconvex optimization with random data ⋮ Debiasing convex regularized estimators and interval estimation in linear models ⋮ Local convexity of the TAP free energy and AMP convergence for \(\mathbb{Z}_2\)-synchronization ⋮ Noisy linear inverse problems under convex constraints: exact risk asymptotics in high dimensions ⋮ Universality of regularized regression estimators in high dimensions ⋮ The Lasso with general Gaussian designs with applications to hypothesis testing ⋮ Optimal linear discriminators for the discrete choice model in growing dimensions ⋮ Precise statistical analysis of classification accuracies for adversarial training ⋮ A Unifying Tutorial on Approximate Message Passing ⋮ Asymptotic normality of robust \(M\)-estimators with convex penalty
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