Abstract. This paper presents algorithms and data structures that exploit a compositional and hierarchical specification to enable more efficient symbolic modelchecking. We encod...
Abstract-- Simultaneously clustering columns and rows (coclustering) of large data matrix is an important problem with wide applications, such as document mining, microarray analys...
Abstract— This paper presents the use of a newly created network structure known as a Self-Delaying Dynamic Network (SDN). The SDNs were created to process data which varies with...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Abstract. Regular model checking is a form of symbolic model checking technique for systems whose states can be represented as finite words over a finite alphabet, where regular ...