Lazy propagation: A junction tree inference algorithm based on lazy evaluation

摘要

In this paper we present a junction tree based inference architecture exploiting the structure of the original Bayesian network and independence relations induced by evidence to improve the efficiency of inference. The efficiency improvements are obtained by maintaining a multiplicative decomposition of clique and separator potentials. Maintaining a multiplicative decomposition of clique and separator potentials offers a tradeoff between off-line constructed junction trees and on-line exploitation of barren variables and independence relations induced by evidence.