Dynamic Control of Session Input Rates in Communication Networks

Gafni, Eli; Bertsekas, Dimitri P.

doi:10.21236/ada133572

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A Linear Time Algorithm For Identifying Independence1

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1990

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“…First, we devise a simple algorithm for the following problem: Given a finite The main difference between this algorithm and BFS, a change that has been proposed by Gafni [7], is the traversal of the graph according to a labeling of the links and not according to a labeling of nodes. This change is essential as the example in Figure 10 shows.…”

Section: A Linear Time Algorithm For Identifying Independencementioning

confidence: 99%

Identifying independence in bayesian networks

1990

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An important feature of Bayesian networks is that they facilitate explicit encoding of information about independencies in the domain, information that is indispensable for efficient inferencing. This article characterizes all independence assertions that logically follow from the topology of a network and develops a linear time algorithm that identifies these assertions. The algorithm's correctness is based on the soundness of a graphical criterion, called d-separation, and its optimality stems from the completeness of dseparation. An enhanced version of d-separation, called D-separation, is defined, extending the algorithm to networks that encode functional dependencies. Finally, the algorithm is shown to work for a broad class of nonprobabilistic independencies.

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Section: A Linear Time Algorithm For Identifying Independencementioning

confidence: 99%