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20092013
most citedA New Algorithm for Finding MAP Assignments to Belief Networks

57 citations · 131 across the 11 of their papers we have counts for

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cs.AI201357 cited

A New Algorithm for Finding MAP Assignments to Belief Networks

Solomon Eyal Shimony, Eugene Charniak

We present a new algorithm for finding maximum a-posterior) (MAP) assignments of values to belief networks. The belief network is compiled into a network consisting only of nodes w…

cs.AI2013

Algorithms for Irrelevance-Based Partial MAPs

Solomon Eyal Shimony

Irrelevance-based partial MAPs are useful constructs for domain-independent explanation using belief networks. We look at two definitions for such partial MAPs, and prove important…

cs.AI2013

Relevant Explanations: Allowing Disjunctive Assignments

Solomon Eyal Shimony

Relevance-based explanation is a scheme in which partial assignments to Bayesian belief network variables are explanations (abductive conclusions). We allow variables to remain una…

cs.AI2013

Belief Updating by Enumerating High-Probability Independence-Based Assignments

Eugene Santos, Solomon Eyal Shimony

Independence-based (IB) assignments to Bayesian belief networks were originally proposed as abductive explanations. IB assignments assign fewer variables in abductive explanations…

cs.AI20137 cited

Sample-and-Accumulate Algorithms for Belief Updating in Bayes Networks

Eugene Santos, Solomon Eyal Shimony, Edward Williams

Belief updating in Bayes nets, a well known computationally hard problem, has recently been approximated by several deterministic algorithms, and by various randomized approximatio…

cs.AI201312 cited

Cost-Sharing in Bayesian Knowledge Bases

Solomon Eyal Shimony, Carmel Domshlak, Eugene Santos

Bayesian knowledge bases (BKBs) are a generalization of Bayes networks and weighted proof graphs (WAODAGs), that allow cycles in the causal graph. Reasoning in BKBs requires findin…