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16

NIPS
2003

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Linear Response for Approximate Inference

13 years 5 months ago

Linear Response for Approximate Inference

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Belief propagation on cyclic graphs is an efﬁcient algorithm for computing approximate marginal probability distributions over single nodes and neighboring nodes in the graph. In this paper we propose two new algorithms for approximating joint probabilities of arbitrary pairs of nodes and prove a number of desirable properties that these estimates fulﬁll. The ﬁrst algorithm is a propagation algorithm which is shown to converge if belief propagation converges to a stable ﬁxed point. The second algorithm is based on matrix inversion. Experiments compare a number of competing methods.

Max Welling, Yee Whye Teh

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Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2003
Where	NIPS
Authors	Max Welling, Yee Whye Teh

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