Abstract-- In this paper we study different distributed estimation schemes for stochastic discrete time linear systems where the communication between the sensors and the estimatio...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Objective: To apply and compare common machine learning techniques with an expert-built Bayesian Network to determine eligibility for asthma guidelines in pediatric emergency depa...
Judith W. Dexheimer, Laura E. Brown, Jeffrey Leego...
Variance is a classical measure of a point estimator's sampling error. In steady-state simulation experiments, many estimators of this variance--or its square root, the stand...
The strategy for natural language interpretation presented in this paper implements the dynamics of context change by translating natural language texts into a meaning representat...