A Simple and Practical Algorithm for Differentially Private Data Release
Abstract
We present a new algorithm for differentially private data release, based on a simple combination of the Exponential Mechanism with the Multiplicative Weights update rule. Our MWEM algorithm achieves what are the best known and nearly optimal theoretical guarantees, while at the same time being simple to implement and experimentally more accurate on actual data sets than existing techniques.
Cite
Text
Hardt et al. "A Simple and Practical Algorithm for Differentially Private Data Release." Neural Information Processing Systems, 2012.Markdown
[Hardt et al. "A Simple and Practical Algorithm for Differentially Private Data Release." Neural Information Processing Systems, 2012.](https://mlanthology.org/neurips/2012/hardt2012neurips-simple/)BibTeX
@inproceedings{hardt2012neurips-simple,
title = {{A Simple and Practical Algorithm for Differentially Private Data Release}},
author = {Hardt, Moritz and Ligett, Katrina and Mcsherry, Frank},
booktitle = {Neural Information Processing Systems},
year = {2012},
pages = {2339-2347},
url = {https://mlanthology.org/neurips/2012/hardt2012neurips-simple/}
}