High-dimensional logistic regression with missing data: Imputation, regularization, and universality

Kabir Aladin Verchand, Andrea Montanari

We study high-dimensional, ridge-regularized logistic regression in a setting in which the covariates may be missing or corrupted by additive noise. When both the covariates and th…