The success of the Lasso in era high-dimensional data can be attributed to its conducting an implicit model selection, that is, zeroing out regression coefficients are not significant. By contrast, classical ridge cannot reveal a potential sparsity parameters, and may also introduce large bias under setting. Nevertheless, recent work on involves debiasing thresholding, latter order further enha...