Which solver to choose depends on the nature of your matrix. SuiteSparse is built on top of LAPACK and BLAS, which are pretty low level and FORTRAN-y.

To improve the stability of macromolecular complexes in vitro, we present a generic method that optimizes the stability, homogeneity and solubility of macromolecular complexes by sparse-matrix ...

This paper considers estimation of sparse covariance matrices and establishes the optimal rate of convergence under a range of matrix operator norm and Bregman divergence losses. A major focus is on ...

JACOB BIEN, ROBERT J. TIBSHIRANI, Sparse estimation of a covariance matrix, Biometrika, Vol. 98, No. 4 (DECEMBER 2011), pp. 807-820 ...

Real PIM systems can provide high levels of parallelism, large aggregate memory bandwidth and low memory access latency, thereby being a good fit to accelerate the widely-used, memory-bound Sparse ...

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 ...