Abstract. Algorithms for probabilistic inference in Bayesian networks are known to have running times that are worst-case exponential in the size of the network. For networks with ...
Johan Kwisthout, Hans L. Bodlaender, Linda C. van ...
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Knowledge of how people interact is important in many disciplines, e.g. organizational behavior, social network analysis, information diffusion and knowledge management applicatio...