This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...
In recent years, mobile ad-hoc networks (MANET’s) have been deployed in various scenarios, but their scalability is severely restricted by the human operators’ ability to conf...
Abstract. In recent years, mobile ad-hoc networks (MANET’s) have been deployed in various scenarios, but their scalability is severely restricted by the human operators’ abilit...
This paper proposes a novel hierarchical clustering method that can classify given data without specified knowledge of the number of classes. In this method, at each node of a hie...
We present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image feature...