most citedA Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer Architectures for Computing Marginals of Probability Distributions

64 citations · 219 across the 17 of their papers we have counts for

collaborators

17 papers

cs.AI2013

Propagation of Belief Functions: A Distributed Approach

Prakash P. Shenoy, Glenn Shafer, Khaled Mellouli

In this paper, we describe a scheme for propagating belief functions in certain kinds of trees using only local computations. This scheme generalizes the computational scheme propo…

cs.AI201311 cited

An Axiomatic Framework for Bayesian and Belief-function Propagation

Prakash P. Shenoy, Glenn Shafer

In this paper, we describe an abstract framework and axioms under which exact local computation of marginals is possible. The primitive objects of the framework are variables and v…

cs.AI201311 cited

Valuation-Based Systems for Discrete Optimization

Prakash P. Shenoy, Glenn Shafer

This paper describes valuation-based systems for representing and solving discrete optimization problems. In valuation-based systems, we represent information in an optimization pr…

cs.AI20131 cited

A Fusion Algorithm for Solving Bayesian Decision Problems

Prakash P. Shenoy

This paper proposes a new method for solving Bayesian decision problems. The method consists of representing a Bayesian decision problem as a valuation-based system and applying a…

cs.AI2013

Conditional Independence in Uncertainty Theories

Prakash P. Shenoy

This paper introduces the notions of independence and conditional independence in valuation-based systems (VBS). VBS is an axiomatic framework capable of representing many differen…

cs.AI2013

Valuation Networks and Conditional Independence

Prakash P. Shenoy

Valuation networks have been proposed as graphical representations of valuation-based systems (VBSs). The VBS framework is able to capture many uncertainty calculi including probab…