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The benefit of this extension is that all single-variable beliefs are computed (approximately) at once, using a two-phase message-passing process along the ...
The paper presents a parameterized approximation scheme for probabilistic inference. The scheme, called Mini-. Clustering (MC), extends the partition-based ...
The benefit of this extension is that all single-variable beliefs are computed (approximately) at once, using a two-phase message-passing process along the ...
In practice, we find that the updates of Algorithm 1 converge when suit- ably relaxed,1 although the convergence rate can be slower than that of ordinary BP.
Approximation structure plays an important role in inference on loopy graphs. As a tractable structure, tree approximations have been utilized.
Cluster graph definition: A data structure that provides a graphical flowchart of the factor manipulation process. Each node is a subset of variables.
This paper presents a new metric-tree algorithm which can be used in the context of POMDP planning to sort belief points spatially, and then perform fast value ...
"Tree Approximation for Belief Updating", In proceedings of AAAI-2002, forthcoming. [R101] PostScript PDF Rina Dechter, Kalev Kask and Robert Mateescu ...
Abstract—We present a tree-based reparameterization (TRP) framework that provides a new conceptual view of a large class of algorithms for computing ...
In this paper, belief propagation is extended to represent fac- tors with tree approximations, by way of the expectation propagation framework. That is, each ...
Missing: Updating. | Show results with:Updating.