Central dp fixed clipping #2765
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mohammadnaseri
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danieljanes and
tanertopal
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panh99
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Jan 3, 2024
| ) -> Tuple[Optional[Parameters], Dict[str, Scalar]]: | ||
| """Aggregate training results using unweighted aggregation.""" | ||
| if failures: | ||
| return None, {} |
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May I know why this DP strategy does not tolerate any failures? Is it fine to proceed with the DP algorithm with a few clients dropping out?
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This makes the epsilon computation afterwards very difficult. As we need to know how many clients were selected on each round. I would say let's keep it this way for now and we can investigate those scenarios.
| @@ -0,0 +1,217 @@ | |||
| # Copyright 2020 Flower Labs GmbH. All Rights Reserved. | |||
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The code looks good. Just a few small things. Btw, could you get past all the CI checks?
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Issue
Description
The implementation of enabling strategies with central differential privacy. It allows the server to clip (with fix value) the updates and add noise to them.
Related issues/PRs
N/A
Proposal
Explanation
Implement a new wrapper class
DPWrapper_fixed_clipping(which itself is a strategy) to first it clips the updates from the clients before passing them to the inner strategy, and second, it adds noise to the aggregated results.Checklist
#contributions)Changelog entry
The strategies now can be wrapped around with a dp class to allow them perform clipping and noise addition.
Any other comments?
N/A