A Block Coordinate Descent Approach for Large scale Sparse Inverse Covariance Estimation

The sparse inverse covariance estimation problem arises in many statistical applications in machine learning and signal processing. In this problem, the inverse of a covariance matrix of a multivariate normal distribution is estimated, assuming that it is sparse.