Abstract: It is often challenging to reconstruct accurately a complete dynamic biological network due to the scarcity of data collected in cost-effective experiments. This paper ad...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Abstract--Wireless networks, especially mobile ad hoc networks (MANET) and cognitive radio networks (CRN), are facing two new challenges beyond traditional random network model: op...
Dynamically discovering likely program invariants from concrete test executions has emerged as a highly promising software engineering technique. Dynamic invariant inference has t...
Christoph Csallner, Nikolai Tillmann, Yannis Smara...
Abstract. In this paper we present static and dynamic studies of duplicate and near-duplicate documents in the Web. The static and dynamic studies involve the analysis of similar c...