We introduce a user-friendly computational framework 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 L$_{2}$E 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. Supplementary materials for this article are available online.
翻译：我们采用方便用户的计算框架,按照L$=%2}标准实施各种结构回归方法的稳健版本;除了采用计算法进行L$2}$E回归外,我们的框架还允许采用“L$2}$标准进行强有力的回归,以补充结构性制约;在不需要精度参数复杂调整程序的情况下开展工作,可以用来确定多种亚群,并可以纳入现成的非紫外结构回归解决器;我们为框架提供趋同保证,并以一些实例展示其灵活性;关于本条的补充材料可在网上查阅。
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