An Introduction to MCMC for Machine Learning

Christophe Andrieu; Nando de Freitas; Arnaud Doucet B; Michael I. Jordan

doi:10.1023/a:1020281327116

An Introduction to MCMC for Machine Learning

Christophe Andrieu (University of Bristol) iD Nando de Freitas (University of British Columbia) iD Arnaud Doucet B (The University of Melbourne) iD Michael I. Jordan (University of California, Berkeley) iD

Journal: Machine Learning • 2003-01-01 • Springer Science+Business Media • ISSN: 0885-6125

Abstract

Abstract text is not embedded in this discovery record. Please consult the full-text publication via the source link on the right.

Subjects & Keywords

# Markov Chains and Monte Carlo Methods # Mathematics # Gaussian Processes and Bayesian Inference # Computer Science # Bayesian Modeling and Causal Inference

How to Cite this Article

                    Christophe Andrieu, Nando de Freitas, Arnaud Doucet B, et al. (2003). "An Introduction to MCMC for Machine Learning". Machine Learning. https://doi.org/10.1023/a:1020281327116                

Access Full Article

Read Original Article ↗ View Source PDF ↗

MainReads is an independent discovery directory. Clicking above directs you to the official publisher repository.

Licence & Open Access

Open Access

Publicly accessible via the publisher or archive. Commercial redistribution or automated full-text duplication without author permission may be restricted.

Identifiers & Provenance

DOI: https://doi.org/10.1023/a:1020281327116 ↗
OpenAlex: W2135194391 ↗
Primary Index: OPENALEX