On the Choice of Regions for Generalized Belief Propagation

Understand

Generalized belief propagation (GBP) has proven to be a promising technique for approximate inference tasks in AI and machine learning.

• However, the choice of a good set of clusters to be used in GBP has remained more of an art then a science until this day.
• This paper proposes a sequential approach to adding new clusters of nodes and their interactions (i.e.
• "regions") to the approximation.