Paper Info
Title
Beliefs in Markov Trees - From Local Computations to Local Valuation.
Abstract
This paper is devoted to expressiveness of hypergraphs for which uncertainty propagation by local computations via Shenoy/Shafer method applies. It is demonstrated that for this propagation method for a given joint belief distribution no valuation of hyperedges of a hypergraph may provide with simpler hypergraph structure than valuation of hyperedges by conditional distributions. This has vital implication that methods recovering belief networks from data have no better alternative for finding the simplest hypergraph structure for belief propagation. A method for recovery tree-structured belief networks has been developed and specialized for Dempster-Shafer belief functions
Year
Venue
Field
2017
arXiv: Artificial Intelligence
Conditional probability distribution,Propagation of uncertainty,Computer science,Hypergraph,Theoretical computer science,Artificial intelligence,Valuation (finance),Computation,Belief propagation,Discrete mathematics,Constraint graph,Markov chain,Machine learning
DocType
Volume
Citations 
Journal
abs/1704.03723
0
PageRank 
References 
Authors
0.34
0
1
Name
Order
Citations
PageRank
Mieczyslaw A. Klopotek136678.58