Sparse Linear Regression when Noises and Covariates are Heavy-Tailed and Contaminated by Outliers

Sparse estimation has been studied extensively over the past 20 ye ars to handle modern high-dimensional data with [ 40 ] as a starting point. Because the advancement of computer tech nology has made it possible to collect very high dimensional data efficiently, sparse estimation will continue to be an important and effective method for high dimensional data an alysis in the future. In this study, we focus on the estimation of coefficients in sparse linear reg ression.