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

The results are then extended to the general matrix l w operator norms for 1 ≤ w ≤ ∞. In addition, we give a unified result on the minimax rate of convergence for sparse covariance matrix estimation ...

There is increasing interest in the study of community detection for sparse networks. Here, we propose a new method for detecting communities in sparse networks that uses the symmetrized Laplacian ...