Gaussian graphical models are of great interest in statistical learning. Because the conditional independencies between different nodes correspond to zero entries in the inverse c...
Abstract. An efficient parallel algorithm is presented and tested for computing selected components of H−1 where H has the structure of a Hamiltonian matrix of two-dimensional la...
Lin Lin, Chao Yang, Jianfeng Lu, Lexing Ying, Wein...
A new software code for computing selected eigenvalues and associated eigenvectors of a real symmetric matrix is described. The eigenvalues are either the smallest or those closes...
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...