# Distributed Parameter Estimation in Probabilistic Graphical Models

arXiv: https://arxiv.org/abs/1406.3070 · HTML: https://mlsanity.com/paper/1406.3070/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jun 2014.

## Built on by (most cited first, 1 of 1)

- [Decentralized Multitask Learning over Learned Task Graphs](https://mlsanity.com/paper/2608.26989/) (2026)

## Abstract (arXiv)

This paper presents foundational theoretical results on distributed parameter estimation for undirected probabilistic graphical models. It introduces a general condition on composite likelihood decompositions of these models which guarantees the global consistency of distributed estimators, provided the local estimators are consistent.