The right complexity measure in locally private estimation: It is not the Fisher information
The right complexity measure in locally private estimation: It is not the Fisher information
We identify fundamental tradeoffs between statistical utility and privacy under local models of privacy in which data is kept private even from the statistician, providing instance-specific bounds for private estimation and learning problems by developing the local minimax risk. In contrast to approaches based on worst-case (minimax) error, which are …