Computing Upper and Lower Bounds on Likelihoods in Intractable Networks

Abstract

We present deterministic techniques for computing upper and lower bounds on marginal probabilities in sigmoid and noisy-OR networks. These techniques become useful when the size of the network (or clique size) precludes exact computations. We illustrate the tightness of the bounds by numerical experiments.

Appears in Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence (UAI1996)

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