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Bayesian Generalized Linear Models in a Terabyte World



Abstract This paper introduces extremely fast approximate infer-ence schemes for Bayesian treatments of dynamic generalized linear models. The approximations are tailored vari-ants of quadrature EP. The first forward pass of this fixed point iteration algorithm can be interpreted as a one-stepunscented Kalman filter. For on-line applications this filter can handle tens of thousands of updates a second on acurrent day desktop machine. 1

Year: 2009
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