This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
The field of intelligent tutoring systems has been using the well known knowledge tracing model, popularized by Corbett and Anderson (1995) to track individual users’ knowledge f...
—This paper presents the design of BAUT, a tutoring system that explores statistical approach for providing instant project failure analysis. Driven by a Bayesian Network (BN) in...
Bayesian Network structures with a maximum in-degree of k can be approximated with respect to a positive scoring metric up to an factor of 1/k. Key words: approximation algorithm,...