—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...
Multiply sectioned Bayesian networks (MSBNs) provide a coherent and flexible formalism for representing uncertain knowledge in large domains. Global consistency among subnets in a...
This paper describes a novel method for explaining Bayesian network (BN) inference when the network is modeling a population of conditionally independent agents, each of which is m...
We describe a Bayesian inference algorithm that can be used to train any cascade of weighted finite-state transducers on end-toend data. We also investigate the problem of automat...
David Chiang, Jonathan Graehl, Kevin Knight, Adam ...
There are many key problems of decision making related to spectrum occupancies in cognitive radio networks. It is known that there exist correlations of spectrum occupancies in tim...