Hui Feng

Convex Reparameterization and Self-Concordant Algorithms for Multivariate Regression with Covariance Estimation

Building on a reparameterization for multivariate linear regression that yields a jointly convex penalized likelihood in the reparameterized regression coefficient matrix and the precision matrix, we show that the resulting scaled Gaussian loss is standard self-concordant. This places the joint estimation problem withi...