Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms. (arXiv:2201.03968v1 [cs.GT])

We consider a platform's problem of collecting data from privacy sensitive
users to estimate an underlying parameter of interest. We formulate this
question as a Bayesian-optimal mechanism design problem, in which an individual
can share her (verifiable) data in exchange for a monetary reward or services,
but at the same time has a (private) heterogeneous privacy cost which we
quantify using differential privacy. We consider two popular differential
privacy settings for providing privacy guarantees for the users: central and
local. …

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