8000 Double-charging privacy in DC-GAN example · Issue #418 · pytorch/opacus · GitHub
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Double-charging privacy in DC-GAN example #418

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ffuuugor opened this issue Apr 25, 2022 · 2 comments
Open

Double-charging privacy in DC-GAN example #418

ffuuugor opened this issue Apr 25, 2022 · 2 comments
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@ffuuugor
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tl;dr: dcgan.py example adds noise to the fake data gradients, which it doesn't need to.
We should change the training pipeline (because it's more correct) and measure the impact (because we're curious).

See more details and solution proposals on the PyTorch forum thread

@karthikprasad karthikprasad added the good first issue Good for newcomers label May 18, 2022
Koukyosyumei added a commit to Koukyosyumei/opacus that referenced this issue Sep 3, 2022
@Koukyosyumei
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Koukyosyumei commented Sep 6, 2022

@ffuuugor

Hi! I'm Hideaki, an undergrad student at the University of Tokyo and a research intern at Tsinghua University on privacy-preserving machine learning. I am currently working on this issue. I've made a PR but need approval from the maintainer to run the workflow. How should I proceed?

@romovpa
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romovpa commented Sep 6, 2022

@Koukyosyumei Thank you for contributing!
We will review it soon. Let's discuss in your PR, I've left a comment.

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