Floating-point Sparse Matrix-Vector Multiplication (SpMXV) is a key computational kernel in scientific and engineering applications. The poor data locality of sparse matrices sig...
A novel parallel algorithm for matrix multiplication is presented. It is based on a 1-D hyper-systolic processor abstraction. The procedure can be implemented on all types of para...
An interesting problem in Nonnegative Matrix Factorization (NMF) is to factorize the matrix X which is of some specific class, for example, binary matrix. In this paper, we exten...
Zhongyuan Zhang, Tao Li, Chris H. Q. Ding, Xiangsu...
Many scientific and engineering applications involve inverting large matrices or solving systems of linear algebraic equations. Solving these problems with proven algorithms for d...
Simon Branford, Cihan Sahin, Ashish Thandavan, Chr...
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...