In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
In this paper, we present a novel active contour model, in which the traditional gradient descent optimization is replaced by graph cut optimization. The basic idea is to first de...
Hang Chang, Qing Yang, Manfred Auer, Bahram Parvin
The aim of this study is to investigate the impact of various pre-processing models on the forecast capability of artificial neural network (ANN) when auditing financial accounts. ...
We introduce Bayesian Expansion (BE), an approximate numerical technique for passage time distribution analysis in queueing networks. BE uses a class of Bayesian networks to appro...
Model driven development (MDD) of software product lines (SPLs) merges two increasing important paradigms that synthesize programs by transformation. MDD creates programs by transf...
Greg Freeman, Don S. Batory, R. Greg Lavender, Jac...