The article explores a method called robust regression using multivariate regression depth functions in contaminated data scenarios. The researchers found that these estimators can achieve optimal rates in various regression problems, such as nonparametric regression and sparse linear regression. They also introduced a new concept of depth function for linear operators that could be useful in robust functional linear regression.