Signal Extraction Approach for Sparse Multivariate Response
Regression // Methods for regression with high-dimensional
predictors and univariate or maltivariate response variables.
It considers the decomposition of the coefficient matrix that
leads to the best approximation to the signal part in the
response given any rank, and estimates the decomposition by
solving a penalized generalized eigenvalue problem followed by
a least squares procedure. Ruiyan Luo and Xin Qi (2017)
doi:10.1016/j.jmva.2016.09.005.