We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
— This paper investigates measures of centrality that are applicable to power grids. Centrality measures are used in network science to rank the relative importance of nodes and ...
Framework-intensive applications (e.g., Web applications) heavily use temporary data structures, often resulting in performance bottlenecks. This paper presents an optimized blend...
Most programs are repetitive, where similar behavior can be seen at different execution times. Algorithms have been proposed that automatically group similar portions of a program...
Containing much valuable information, networks such as the World Wide Web, social networks and metabolic networks draw increasingly attention in scientific communities. Network cl...