MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization

TheMixedRegression(MR)problem considers theestimation ofK functions fromacollection of input-output samples, where for each sample, the output is generated by one of theK regression functions. When fitting linear functions in a noiseless setting, this is equivalent to solvingK linear systems, while at the same time, identifying which system each equation belongs to. The MR formulation can be employed as an approach to decompose a complicated function intoK simpler ones, by splitting the observations intoK classes.