626_privacy/tensorflow_privacy
2
0
Fork 1
Code Issues Pull requests 1 Projects Releases Packages Wiki Activity Actions
Fork of github.com/tensorflow/privacy
7 commits 2 branches 0 tags 3.1 MiB
Python 69.4%
Jupyter Notebook 28%
Starlark 1.6%
Shell 1%
Find a file
A. Unique TensorFlower ceee90b1ac Add GaussianSumQuery and express GaussianAverageQuery in terms of it. 
Also:
1. Add unit tests for both types of query.
2. Add function "get_query_result" to PrivateQuery. (The utility of having this function is made clear in the test class, where the function _run_query operates on either GaussianSum- or GaussianAverageQueries.)
PiperOrigin-RevId: 225609398
2018-12-18 15:41:38 -08:00
privacy/optimizers Add GaussianSumQuery and express GaussianAverageQuery in terms of it. 2018-12-18 15:41:38 -08:00
CONTRIBUTING.md Project import generated by Copybara. 2018-12-02 13:07:04 -08:00
LICENSE Project import generated by Copybara. 2018-12-02 13:07:04 -08:00
README.md PiperOrigin-RevId: 224061027 2018-12-04 17:01:39 -08:00
requirements.txt Update to allow bazel on tensorflow_privacy to work out of the box. 2018-12-18 15:41:26 -08:00

README.md

TensorFlow Privacy

This repository will contain implementations of TensorFlow optimizers that support training machine learning models with (differential) privacy, as well as tutorials and analysis tools for computing the privacy guarantees provided.

The content of this repository will supersede the following existing repository: https://github.com/tensorflow/models/tree/master/research/differential_privacy