Distributed Parameter Estimation in Probabilistic Graphical Models

摘要

This paper presents foundational theoretical results on distributed parameterestimation for undirected probabilistic graphical models. It introduces ageneral condition on composite likelihood decompositions of these models whichguarantees the global consistency of distributed estimators, provided the localestimators are consistent.