Non-Convex Global Minimization and False Discovery Rate Control for the TREX
Non-Convex Global Minimization and False Discovery Rate Control for the TREX
The TREX is a recently introduced method for performing sparse high-dimensional regression. Despite its statistical promise as an alternative to the lasso, square-root lasso, and scaled lasso, the TREX is computationally challenging in that it requires solving a non-convex optimization problem. This paper shows a remarkable result: despite the non-convexity …