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[Differential privacy](https://en.wikipedia.org/wiki/Differential_privacy) provides a way to analyze large data-sets without violating the privacy of individuals.
Adjusting the scoring of the rubr…
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At the moment, the spec thinks of a PA task as a one-way data-processing pipeline with three phases: upload, in which clients send inputs to the leader; verify, in which the leader and helper verify e…
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Hi,
Thanks for your framework. I tried to run your code but get this error "TypeError: Values of type * cannot be cast to type *" when loading emnist data. Do you know how I can fix it? Thanks.
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Based on https://make.wordpress.org/core/2021/04/18/proposal-treat-floc-as-a-security-concern/ and other published concerns, it seems wise to treat FLoC as something that site owners should explicitly…
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This decision takes a step back to align on what features we should support in a version 0, and why.
We are eventually targeting multiple levels of protection (lacking names for these versions as o…
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## Description
We'd like to upgrade the demo from #3768 to support Differentially Private Learning.
## Breakdown
- Identify and select theories/methods of differential privacy that respond to our…
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I've followed build instructions, and encountered a build failure.
```
~/differential-privacy/cc main ❯ bazel build "..." 13:08:04
INFO:…
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### Brief Summary:
Describe the what, why, and how of your content idea in 2-5 sentences.
Differential privacy is a system for publicly sharing information about a dataset by describing the patte…
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The local differential privacy from UVM will not be ready on day 1 of course, so we should prepare ways to inject something similar into our generative pipelines. This can include various kinds of noi…
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Thanks for open sourcing this library!
As a newcomer to bazel, I've spent quite a while getting it to build and then getting `CREATE EXTENSION anon_func` to work, and I think highlighting two things …