Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
As the complexity of Internet is scaled up, it is likely for the Internet resources to be exposed to Distributed Denial of Service (DDoS) flooding attacks on TCP-based Web servers....
Experience from the management of distributed computer-based learning resources in schools has been proven to be inefficient and costly. Though commercial software packages are av...
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Over the last decade, programmable Network Processors (NPs) have become widely used in Internet routers and other network components. NPs enable rapid development of complex packe...
Charlie Wiseman, Jonathan S. Turner, Michela Becch...