Improved estimators for semi-supervised high-dimensional regression model
Improved estimators for semi-supervised high-dimensional regression model
We study a high-dimensional linear regression model in a semi-supervised setting, where for many observations only the vector of covariates X is given with no responses Y. We do not make any sparsity assumptions on the vector of coefficients, nor do we assume normality of the covariates. We aim at …