User-Specified Local Differential Privacy in Unconstrained Adaptive Online Learning

Neural Information Processing Systems 

Local differential privacy is a strong notion of privacy in which the provider of the data guarantees privacy by perturbing the data with random noise. In the standard application of local differential privacy the distribution of the noise is constant and known by the learner.

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