In this paper, we study the problem of information preservation when decomposing a single Bayesian network into a set of smaller Bayesian networks. We present a method that losslessly decomposes a Bayesian network so that no conditional independency information is lost and no extraneous conditional independency information is introduced during the decomposition.

This research introduces a new strategy in cluster ensemble selection by using Independency and Diversity metrics. In recent years, Diversity and Quality, which are two metrics in evaluation procedure, have been used for selecting basic clustering results in the cluster ensemble selection. Although quality can improve the final results in cluster ensemble, it cannot control the procedures of ge...

A spanning tree of a connected graph G is said to be an independency tree if all its endvertices are pairwise nonadjacent in G. We prove that a connected graph G has no independency tree if and only if G is a cycle, a complete graph or a complete bipartite graph the color classes of which have equal cardinality.

To the best knowledge of authors, none of existing literatures is available for the linear independency test of interval vectors. In this note, we present an effective way for checking the linear independency of interval vectors and its possible application to the robust control problem, for example in this note, for solve the robust controllability test and robust observability test of uncerta...

9] S.L. Lauritzen and D.J. Spiegelhalter. Local computations with probabilities on graphical structures and their applications to expert systems (with discussion). 13 algorithms currently known for inference in probabilistic networks. IDAGs can also be helpful for constructing a DAG from a given independency model. For the construction of a DAG from an independency model, in 1] an algorithm has...