use for constraint solving, abstract interpretation, spatial databases, and theorem proving. In this paper we develop new incremental algorithms for UTVPI constraint satisfaction a...
We introduce a “derandomized” analogue of graph squaring. This operation increases the connectivity of the graph (as measured by the second eigenvalue) almost as well as squar...
We revisit and use the dependence transformation method to generate parallel algorithms suitable for cluster and grid computing. We illustrate this method in two applications: to o...
Ulisses Kendi Hayashida, Kunio Okuda, Jairo Panett...
Karp and Zhang developed a general randomized parallel algorithm for solving branch and bound problems. They showed that with high probability their algorithm attained optimal spe...
Compressed sensing or compressive sampling (CS) has been receiving a lot of interest as a promising method for signal recovery and sampling. CS problems can be cast as convex prob...
Seung-Jean Kim, Kwangmoo Koh, Michael Lustig, Step...