Approximate Inference A lgorithms for Two-Layer Bayesian Networks

Ng, Andrew Y., Jordan, Michael I.

Neural Information Processing Systems 

We present a class of approximate inference algorithms for graphical models of the QMR-DT type. We give convergence rates for these algorithms andfor the Jaakkola and Jordan (1999) algorithm, and verify these theoretical predictions empirically.

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