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One of the barriers to using belief networks for medical information retrieval is the computational cost of reasoning as the networks become large. Stochastic simulation algorithms allow one to compute approximations of probability values in a reasonable amount of time. We previously examined the performance of five stochastic simulation algorithms applied(More)
In this paper we present a new formulation of the Support Vector Machine for classifying data. It is based on development of ideas from methods of total least squares, in which error in measured data is incorporated in the model design. The new formulation studied is similar to the soft margin SVM, but has to be solved using nonlinear optimization rather(More)
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