This paper presents language features for High Performance Fortran HPF to specify non-local access patterns of distributed arrays, called halos, and to control the communication as...
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
The simulation of wide area computer networks is one area where the benefits of parallel simulation have been clearly demonstrated. Here we present a description of a system that...
Branch, cut, and price (BCP) is an LP-based branch and bound technique for solving large-scale discrete optimization problems (DOPs). In BCP, both cuts and variables can be generat...
Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors a...