Greedy Importance Sampling
Abstract
I present a simple variation of importance sampling that explicitly search(cid:173) es for important regions in the target distribution. I prove that the tech(cid:173) nique yields unbiased estimates, and show empirically it can reduce the variance of standard Monte Carlo estimators. This is achieved by con(cid:173) centrating samples in more significant regions of the sample space.
Cite
Text
Schuurmans. "Greedy Importance Sampling." Neural Information Processing Systems, 1999.Markdown
[Schuurmans. "Greedy Importance Sampling." Neural Information Processing Systems, 1999.](https://mlanthology.org/neurips/1999/schuurmans1999neurips-greedy/)BibTeX
@inproceedings{schuurmans1999neurips-greedy,
title = {{Greedy Importance Sampling}},
author = {Schuurmans, Dale},
booktitle = {Neural Information Processing Systems},
year = {1999},
pages = {596-602},
url = {https://mlanthology.org/neurips/1999/schuurmans1999neurips-greedy/}
}