ML Anthology

An Introduction to MCMC for Machine Learning

Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan
MLJ 2003 pp. 5-43
doi:10.1023/A:1020281327116 /mlj/2003/andrieu2003mlj-introduction/

Abstract

This purpose of this introductory paper is threefold. First, it introduces the Monte Carlo method with emphasis on probabilistic machine learning. Second, it reviews the main building blocks of modern Markov chain Monte Carlo simulation, thereby providing and introduction to the remaining papers of this special issue. Lastly, it discusses new interesting research horizons.

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Cite

Text

Andrieu et al. "An Introduction to MCMC for Machine Learning." Machine Learning, 2003. doi:10.1023/A:1020281327116

Markdown

[Andrieu et al. "An Introduction to MCMC for Machine Learning." Machine Learning, 2003.](https://mlanthology.org/mlj/2003/andrieu2003mlj-introduction/) doi:10.1023/A:1020281327116

BibTeX

@article{andrieu2003mlj-introduction,
  title     = {{An Introduction to MCMC for Machine Learning}},
  author    = {Andrieu, Christophe and de Freitas, Nando and Doucet, Arnaud and Jordan, Michael I.},
  journal   = {Machine Learning},
  year      = {2003},
  pages     = {5-43},
  doi       = {10.1023/A:1020281327116},
  volume    = {50},
  url       = {https://mlanthology.org/mlj/2003/andrieu2003mlj-introduction/}
}