Research map / Federated learning and privacy / Differential privacy
Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Cap user contributions at the (1 - 1/(n·eps))-quantile (the 1/eps-th largest value) instead of the median or 95% quantile before Laplace mechanism for summing | private sum of MovieLens 20M rating counts · MovieLens 20M, private sum estimation | relative error | Helped |
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