By Joe Suzuki, Maomi Ueno

This quantity constitutes the refereed court cases of the second one overseas Workshop on complex Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015.

The 18 revised complete papers and six invited abstracts awarded have been rigorously reviewed and chosen from quite a few submissions. within the overseas Workshop on complicated Methodologies for Bayesian Networks (AMBN), the researchers discover methodologies for boosting the effectiveness of graphical versions together with modeling, reasoning, version choice, logic-probability relatives, and causality. The exploration of methodologies is complemented discussions of sensible concerns for utilizing graphical versions in genuine global settings, overlaying issues like scalability, incremental studying, parallelization, and so on.

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Then, an auxiliary BN model incorporating both data and parameter constraints is constructed. Finally, the optimal parameters are computed as the mean values of the probability distribution, which is inferred by a dynamic discretization junction tree method. Generally, existing methods take the global optimal solution of the constrained optimization problem as the final parameters. However, when the available data is limited, objective function constructed from the data, like likelihood function, will overfit the data.

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