Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
In this paper we consider the consistency problem of temporal or spatial qualitive constraint networks. A new encoding making it possible to represent and solve this problem in th...
In this paper, evolution strategy is applied in order to improve the time series prediction accuracy of a Sugeno and Takagi type fuzzy inference system FIS. The presented approach...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
Shrinking devices to the nanoscale, increasing integration densities, and reducing of voltage levels down to the thermal limit, all conspire to produce faulty systems. Frequent oc...
Kundan Nepal, R. Iris Bahar, Joseph L. Mundy, Will...