Regularization Parameter Selection for the Low Rank Matrix Recovery

A popular approach to recover low rank matrices is the nuclear norm regularized minimization (NRM) for which selection of regularization parameter inevitable. In this paper, we build up a novel rule choose NRM, with help duality theory. Our result provides safe set when solution has an upper bound. Furthermore, apply idea NRM quadratic and Huber functions, establish simple formulae parameters. Finally, report numerical results on some signal shapes by embedding our into cross validation, state that can reduce computational time parameter. To best knowledge, first attempt select matrix recovery.