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Adds instructions on installing the latest version and links to blog posts.

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David Marn 2021-02-08 02:38:57 -08:00 committed by A. Unique TensorFlower
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tensorflow_privacy/privacy/membership_inference_attack/README.md
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@ -18,6 +18,12 @@ the model are used (e.g., losses, logits, predictions). Neither model internals
## How to use
### Installation notes
To use the latest version of the MIA library, please install TF Privacy with
"pip install -U git+https://github.com/tensorflow/privacy". See
https://github.com/tensorflow/privacy/issues/151 for more details.
### Basic usage
The simplest possible usage is
@ -235,6 +241,17 @@ print(attacks_result.calculate_pd_dataframe())
# 25 correctly_classfied False lr 0.370713 0.737148
```
### External guides / press mentions
* [Introductory blog post](https://franziska-boenisch.de/posts/2021/01/membership-inference/)
to the theory and the library by Franziska Boenisch from the Fraunhofer AISEC
institute.
* [Google AI Blog Post](https://ai.googleblog.com/2021/01/google-research-looking-back-at-2020.html#ResponsibleAI)
* [TensorFlow Blog Post](https://blog.tensorflow.org/2020/06/introducing-new-privacy-testing-library.html)
* [VentureBeat article](https://venturebeat.com/2020/06/24/google-releases-experimental-tensorflow-module-that-tests-the-privacy-of-ai-models/)
* [Tech Xplore article](https://techxplore.com/news/2020-06-google-tensorflow-privacy-module.html)
## Contact / Feedback
Fill out this
@ -249,4 +266,4 @@ If you wish to add novel attacks to the attack library, please check our
## Copyright
Copyright 2020 - Google LLC
Copyright 2021 - Google LLC