A stability-derived update formula for a generalized debiased Lasso yields asymptotically accurate approximations for most coordinates under sub-Gaussian designs in the proportional regime, enabling faster resampling-based variable selection.
Concentration of empirical distribution functions with applications to non-iid models
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Stability of a Generalized Debiased Lasso with Applications to Resampling-Based Variable Selection
A stability-derived update formula for a generalized debiased Lasso yields asymptotically accurate approximations for most coordinates under sub-Gaussian designs in the proportional regime, enabling faster resampling-based variable selection.