Exact Inference with Approximate Computation for Differentially Private Data via Perturbations

Ruobin Gong discusses approximate Bayesian computation, a practical suite of methods to simulate from approximate posterior distributions of complex Bayesian models, produces exact posterior samples when applied to differentially private perturbation data.

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