Precision matrix is of significant importance in a wide range of applications in multivariate analysis. This paper considers adaptive minimax estimation of sparse precision matrices in the high ...

Publication title Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests Purdue author Faming Liang Authors Bochao Jia, Faming Liang Publisher Chapman & Hall ...

SparseP software package provides 25 SpMV kernels for real PIM systems supporting the four most widely used compressed matrix formats, and a wide range of data types. Our extensive evaluation provides ...

The matrix-variate normal distribution is a popular model for high-dimensional transposable data because it decomposes the dependence structure of the random matrix into the Kronecker product of two ...