forked from 626_privacy/tensorflow_privacy
Adds instructions on installing the latest version and links to blog posts.
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@ -18,6 +18,12 @@ the model are used (e.g., losses, logits, predictions). Neither model internals
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## How to use
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## How to use
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### Installation notes
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To use the latest version of the MIA library, please install TF Privacy with
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"pip install -U git+https://github.com/tensorflow/privacy". See
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https://github.com/tensorflow/privacy/issues/151 for more details.
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### Basic usage
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### Basic usage
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The simplest possible usage is
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The simplest possible usage is
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@ -235,6 +241,17 @@ print(attacks_result.calculate_pd_dataframe())
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# 25 correctly_classfied False lr 0.370713 0.737148
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# 25 correctly_classfied False lr 0.370713 0.737148
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```
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```
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### External guides / press mentions
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* [Introductory blog post](https://franziska-boenisch.de/posts/2021/01/membership-inference/)
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to the theory and the library by Franziska Boenisch from the Fraunhofer AISEC
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institute.
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* [Google AI Blog Post](https://ai.googleblog.com/2021/01/google-research-looking-back-at-2020.html#ResponsibleAI)
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* [TensorFlow Blog Post](https://blog.tensorflow.org/2020/06/introducing-new-privacy-testing-library.html)
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* [VentureBeat article](https://venturebeat.com/2020/06/24/google-releases-experimental-tensorflow-module-that-tests-the-privacy-of-ai-models/)
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* [Tech Xplore article](https://techxplore.com/news/2020-06-google-tensorflow-privacy-module.html)
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## Contact / Feedback
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## Contact / Feedback
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Fill out this
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Fill out this
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@ -249,4 +266,4 @@ If you wish to add novel attacks to the attack library, please check our
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## Copyright
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## Copyright
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Copyright 2020 - Google LLC
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Copyright 2021 - Google LLC
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