Learn what are the benefits and limitations of using sparse matrices in numerical linear algebra, and how to handle them efficiently and accurately.

A collection of C programs for creating, displaying and converting sparse matrices into efficient formats - jackr276/Sparse-Matrix-Utilities ...

Sparse linear arrays serve as the fundamental basis for sparse signal processing and have demonstrated remarkable direction-of-arrival (DOA) estimation performance. Due to the merit of resolving more ...

We investigate the performance of algorithms for sparse tensor-sparse tensor multiplication (SpGETT). This operation, also called sparse tensor contraction, is a higher order analogue of the sparse ...

Sparse matrix computations are pivotal to advancing high-performance scientific applications, particularly as modern numerical simulations and data analyses demand efficient management of large ...

In particular, we penalize the likelihood with a lasso penalty on the entries of the covariance matrix. This penalty plays two important roles: it reduces the effective number of parameters, which is ...