Shrinkage to Infinity: Reducing Test Error by Inflating the Minimum Norm Interpolator in Linear Models

Jake Freeman

Hastie et al. (2022) found that ridge regularization is essential in high dimensional linear regression $y={\beta }^{T}x+\epsilon$ with isotropic co-variates $x\in {\mathbb{R}}^d$ and $n$ samples…