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Bayesian networks (BNs) are knowledge representation tools capable of representing dependence or independence relationships among random variables that compose a problem domain. Bayesian networks learned from data sets are receiving increasing attention within the community of researchers of uncertainty in artificial intelligence, due to their capacity to provide good inference models and to discover...
As a popular and competent kernel function in kernel based machine learning techniques, conventional Gaussian kernel has unified kernel width with each of basis functions, which make impliedly a basic assumption: the response signal represents below certain frequency and the noise represents above such certain frequency. However, in many case, this assumption does not hold. To overcome this limitation,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.