Doubly Regularized Matrix-Variate Regression // The doubly regularized matrix-variate regression solves a low-rank-plus- sparse structure for matrix-variate generalized linear models through a weighted combination of nuclear-norm and L1-norm. The methodology implemented by this package is described in the paper "Doubly Regularized Matrix-Variate Regression", which has been tentatively accepted for publication but does not yet have a DOI or URL. A formal citation will be added in a future update once the final publication details are available.