Priv'IT: Private and sample efficient identity testing
© 2017 by the author(s). We develop differentially private hypothesis testing methods for the small sample regime. Given a sample V from a categorical distribution p over some domain ∑, an explicitly described distribution q over ∑, some privacy parameter e, accuracy parameter ϵ, and requirements βI...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2022
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| Online Access: | https://hdl.handle.net/1721.1/143458 |