Frontiers in artificial intelligence and applications ;
Dissertations in artificial intelligence
v. 168
Includes bibliographical references (pages [133]-137)
Random variables and conditional independence -- Graph theory -- Markov properties -- Bayesian networks -- Bayesian network specification -- Learning Bayesian networks from data -- Learning parameters -- Learning models -- Monte Carlo methods -- Markov chain Monte Carlo : MCMC -- Learning models via MCMC -- Learning from incomplete data -- Principled iterative methods -- Ad-hoc and heuristic methods