Applications structured as parallel task graphs exhibit both data and task parallelism, and arise in many domains. Scheduling these applications on parallel platforms has been a lo...
We introduce a new technique that can reduce any
higher-order Markov random field with binary labels into
a first-order one that has the same minima as the original.
Moreover, w...
Abstract. The problem of clustering data can be formulated as a graph partitioning problem. In this setting, spectral methods for obtaining optimal solutions have received a lot of...
Marcus Weber, Wasinee Rungsarityotin, Alexander Sc...
Both document clustering and word clustering are well studied problems. Most existing algorithms cluster documents and words separately but not simultaneously. In this paper we pr...
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...