We discuss Bayesian methods for learning Bayesian networks when data sets are incomplete. In particular, we examine asymptotic approximations for the marginal likelihood of incomp...
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
—An important challenge in mobile sensor networks is to enable energy-efficient communication over a diversity of distances while being robust to wireless effects caused by node...
Jeremy Gummeson, Deepak Ganesan, Mark D. Corner, P...
Fuel moisture content (FMC) is one of the variables that drive fire danger. Artificial Neural Networks (ANN) were tested to estimate FMC by calculating the two variables implicat...
: This paper presents a document recommendation system based on clustering peer-to-peer networks. It's an unstructured P2P system. In this system each agent-peer can learn use...