abstract such additional information as network annotations. We introduce a network topology modeling framework that treats annotations as an extended correlation profile of a net...
Xenofontas A. Dimitropoulos, Dmitri V. Krioukov, A...
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
Background: Finding the subgraphs of a graph database that are isomorphic to a given query graph has practical applications in several fields, from cheminformatics to image unders...
Raffaele Di Natale, Alfredo Ferro, Rosalba Giugno,...
We investigate network management information for light-path assessment to dynamically set up end-to-end lightpaths across administrative domains. Our focus is on invetigating what...
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...