Uncertainty in Artificial Intelligence
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Computing Upper and Lower Bounds on Likelihoods in Intractable Networks
Tommi Jaakkola, Michael Jordan
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.
Keywords: Approximate inference, likelihood bounds, Noisy-OR networks, sigmoid networks.
Pages: 340-348
PS Link: ftp://psyche.mit.edu/pub/tommi/jaak-ul-bounds.ps
PDF Link: /papers/96/p340-jaakkola.pdf
BibTex:
@INPROCEEDINGS{Jaakkola96,
AUTHOR = "Tommi Jaakkola and Michael Jordan",
TITLE = "Computing Upper and Lower Bounds on Likelihoods in Intractable Networks",
BOOKTITLE = "Proceedings of the Twelfth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-96)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1996",
PAGES = "340--348"
}


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