—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
Several message passing-based parallel solvers have been developed for general (non-symmetric) sparse LU factorization with partial pivoting. Due to the fine-grain synchronizatio...
A straightforward discretisation of problems in d spatial dimensions often leads to an exponential growth in the number of degrees of freedom. Thus, even efficient algorithms like ...
Abstract: The problem of discovering association rules in large databases has received considerable research attention. Much research has examined the exhaustive discovery of all a...
—Beyond signal processing applications, frames are also powerful tools for modeling the sensing and information processing of many biological and man-made systems that exhibit in...