Research map / Federated learning and privacy / Differential privacy
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace the sample-and-aggregate reduction with a private analogue of the Achlioptas–McSherry algorithm | Learning separated Gaussian mixtures · Separated bounded Gaussian mixtures | sample complexity | Helped |
| Use sample-and-aggregate instead of the proposed algorithm | Learning Gaussian mixtures · Separated bounded Gaussian mixtures | sample complexity: roughly Õ(√d/ε) times | Hurt |
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