A Blessing of Dimensionality: Measure Concentration and Probabilistic Inference
Abstract
This paper proposes an efficient sampling method for inference in probabilistic graphical models. The method exploits a blessing of dimensionality known as the concentration of measure phenomenon in order to derive analytic expressions for proposal distributions. The method can also be interpreted in a variational setting, were one minimises an upperbound on the estimator variance. The results on simple settings are very promising. We believe this method has great potential in graphical models used for diagnosis.
Cite
Text
Muyan and Freitas. "A Blessing of Dimensionality: Measure Concentration and Probabilistic Inference." Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003.Markdown
[Muyan and Freitas. "A Blessing of Dimensionality: Measure Concentration and Probabilistic Inference." Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003.](https://mlanthology.org/aistats/2003/muyan2003aistats-blessing/)BibTeX
@inproceedings{muyan2003aistats-blessing,
title = {{A Blessing of Dimensionality: Measure Concentration and Probabilistic Inference}},
author = {Muyan, Pinar and Freitas, Nando},
booktitle = {Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics},
year = {2003},
pages = {217-224},
volume = {R4},
url = {https://mlanthology.org/aistats/2003/muyan2003aistats-blessing/}
}