- Weiguang Wang, Yingbin Liang, E. Xing. 2013. Block Regularized Lasso for Multivariate Multi-Response Linear Regression. Abstract: The multivariate multi-response (MVMR) linear regression problem is investigated, in which design matrices are Gaussian with covariance matrices (1:K) = (1) ;:::; (K) for K linear regressions. The support union of K p-dimensional regression vectors (collected as columns of matrix B ) are recovered using l1=l2-regularized Lasso. Sucient and necessary conditions to guarantee successful recovery of the support union are characterized via a threshold. More specifically, it is shown that under certain conditions on the distributions of design matri
