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Statistical and machine learning theory has developed several conditions ensuring that popular estimators such as the Lasso or the Dantzig selector perform well in high-dimensional sparse regression, including the restricted eigenvalue, compatibility, and $$\ell _q$$ ℓ q sensitivity properties. However, some of the central aspects of these conditions are not well understood. For instance,...
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