Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to perform poorly on modern processors, largely because of its high ratio of memory op...
The problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science. Examples in computer vision...
Algorithms for the sparse matrix-vector multiplication (shortly SpM×V ) are important building blocks in solvers of sparse systems of linear equations. Due to matrix sparsity, the...
A simultaneous space-time variational formulation of a parabolic evolution problem is solved with an adaptive wavelet method. This method is shown to converge with the best possibl...
Abstract— We consider the approximate sparse recovery problem, where the goal is to (approximately) recover a highdimensional vector x ∈ Rn from its lower-dimensional sketch Ax...