ML Anthology

Distributed Parameter Estimation in Probabilistic Graphical Models

Yariv D Mizrahi, Misha Denil, Nando de Freitas
NeurIPS 2014 pp. 1700-1708
/neurips/2014/mizrahi2014neurips-distributed/

Abstract

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.

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Cite

Text

Mizrahi et al. "Distributed Parameter Estimation in Probabilistic Graphical Models." Neural Information Processing Systems, 2014.

Markdown

[Mizrahi et al. "Distributed Parameter Estimation in Probabilistic Graphical Models." Neural Information Processing Systems, 2014.](https://mlanthology.org/neurips/2014/mizrahi2014neurips-distributed/)

BibTeX

@inproceedings{mizrahi2014neurips-distributed,
  title     = {{Distributed Parameter Estimation in Probabilistic Graphical Models}},
  author    = {Mizrahi, Yariv D and Denil, Misha and de Freitas, Nando},
  booktitle = {Neural Information Processing Systems},
  year      = {2014},
  pages     = {1700-1708},
  url       = {https://mlanthology.org/neurips/2014/mizrahi2014neurips-distributed/}
}