The inertia of an n × n matrix A is defined as the triple (i+(A), i−(A), i0(A)), where i+(A), i−(A), and i0(A) are the number of eigenvalues of A, counting multiplicities, w...
This article presents rigorous normwise perturbation bounds for the Cholesky, LU and QR factorizations with normwise or componentwise perturbations in the given matrix. The conside...
Finding latent factors of the data using matrix factorizations is a tried-and-tested approach in data mining. But finding shared factors over multiple matrices is more novel prob...
Abstract. The functional performance model (FPM) of heterogeneous processors has proven to be more realistic than the traditional models because it integrates many important featur...
Wigderson and Xiao presented an efficient derandomization of the matrix Chernoff bound using the method of pessimistic estimators [WX08]. Building on their construction, we prese...