Pattern-Guided Adaptive Prior for Structure Learning
This paper provides a theoretical analysis of the impact of deviation in edge weights during the optimization process of structure learning and proposes the PGAP framework, which detects two special graph patterns that arise due to the deviation and shows that their occurrence increases as the degree of deviation grows...