B0668
Title: A user-friendly computational framework for robust structured regression with the $L_2$ criterion
Authors: Eric Chi - Rice University (United States) [presenting]
Xiaoqian Liu - University of Texas MD (United States)
Jocelyn Chi - UCLA (United States)
Kenneth Lange - UCLA (United States)
Abstract: A user-friendly computational framework is introduced for implementing robust versions of a wide variety of structured regression methods with the $L_2$ criterion. In addition to introducing an algorithm for performing L2E regression, our framework enables robust regression with the $L_2$ criterion for additional structural constraints, works without requiring complex tuning procedures on the precision parameter, can be used to identify heterogeneous subpopulations, and can incorporate readily available non-robust structured regression solvers. We provide convergence guarantees for the framework and demonstrate its flexibility with some examples.
