We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
Statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the Internet. Calculating man...
RFID tags are being used in many diverse applications in increasingly large numbers. These capabilities of these tags span from very dumb passive tags to smart active tags, with t...
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
For rapid and effective recovery from a flood disaster, an anti-disaster headquarters must not only assess the extent of damage, but also possess overall knowledge of the possibl...