Univariate Polynomial Inference by Monte Carlo Message Length Approximation

Fitzgibbon, Leigh J.; Dowe, David L.; Allison, Lloyd

Univariate Polynomial Inference by Monte Carlo Message Length Approximation

Leigh J. Fitzgibbon, David L. Dowe, Lloyd Allison

ICML 2002 pp. 147-154

/icml/2002/fitzgibbon2002icml-univariate/

Abstract

We apply the Message from Monte Carlo (MMC) algorithm to inference of univariate polynomials. MMC is an algorithm for point estimation from a Bayesian posterior sample.

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Text

Fitzgibbon et al. "Univariate Polynomial Inference by Monte Carlo Message Length Approximation." International Conference on Machine Learning, 2002.

Markdown

[Fitzgibbon et al. "Univariate Polynomial Inference by Monte Carlo Message Length Approximation." International Conference on Machine Learning, 2002.](https://mlanthology.org/icml/2002/fitzgibbon2002icml-univariate/)

BibTeX

@inproceedings{fitzgibbon2002icml-univariate,
  title     = {{Univariate Polynomial Inference by Monte Carlo Message Length Approximation}},
  author    = {Fitzgibbon, Leigh J. and Dowe, David L. and Allison, Lloyd},
  booktitle = {International Conference on Machine Learning},
  year      = {2002},
  pages     = {147-154},
  url       = {https://mlanthology.org/icml/2002/fitzgibbon2002icml-univariate/}
}