In this chapter, we discuss a widely used fault-tolerant data replication model called virtual synchrony. The model responds to two kinds of needs. First, there is the practical qu...
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
In this paper, we formally define the problem of topic modeling with network structure (TMN). We propose a novel solution to this problem, which regularizes a statistical topic mo...
Background: In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interact...
— Monitoring the traffic in high-speed networks is a data intensive problem. Uniform packet sampling is the most popular technique for reducing the amount of data the network mo...