Comments (2)
Good question. The "group_size" parameter there was part of the initial design. It's not implemented yet besides the default value of 1. In particular, supporting group composition for a generic mechanism having approx DP, Renyi DP, f-DP, privacy profile etc all together requires some thoughts and design that we don't have time for right now. But it will be added in the months to come.
For now, I suggest setting the "sensitivity" parameter according to your required group size. Simply increasing the calculated noise scale by sqrt{n} may or may not be valid.
Generally speaking, the parameters inside the Mechanism class should not be modified externally. They are "private attributes" in C++ terms. Use a Mechanism object only by the "public method" would be the right way to go.
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I will not close this for now because this is to be solved by adding a "TransformerZoo.GroupComposition"
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Related Issues (19)
- issue with "privacy_calibrator.subsample_epsdelta_inverse(eps,delta,prob=gamma)" HOT 1
- difference between eps using this method and abadi HOT 3
- Slow privacy calibration
- huge fan of this work
- documentation question HOT 2
- Pure Fdp gaussian mechanism doesn't work under composition of multiple rounds HOT 1
- Issue with SSP_scale and AdaSSP_scale inheritance HOT 2
- Amplification with sampling without replacments is throwing following error. HOT 4
- AFA of composition of subsampled Laplace Mechanism breaks down HOT 1
- Composing different mechanism with different sensitivies HOT 5
- About the bisection method used for converting RDP to approximate DP HOT 1
- Can't install in GBK locale HOT 1
- Looseness in analytic Gaussian mechanism? HOT 3
- `bounds` cannot be used together with `method=Brent` in latest version of scipy (>= v1.10.1) HOT 4
- Can PATE be used in knowledge distillation to calculate privacy budgets?
- Update Installation Instructions HOT 3
- An issue when I installed "autodp": Preparing metadata (setup.py) ... error HOT 2
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