In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
Although a large body of work are devoted to finding communities in static social networks, only a few studies examined the dynamics of communities in evolving social networks. I...
We represent switching activity in VLSI circuits using a graphical probabilistic model based on Cascaded Bayesian Networks (CBN’s). We develop an elegant method for maintaining ...
Abstract. Massive real-world data are network-structured, such as social network, relationship between proteins and power grid. Discovering the latent communities is a useful way f...
In this paper, we describe a dynamic Bayesian network or DBN based approach to both two-hand gestures and onehand gestures. Unlike wired glove-based approaches, the success of cam...