For histograms whose bins each have probability at least alpha, Laplace-perturbed counts leak at most 2/b - log(1 - alpha + alpha e^(2/b)) per record, independent of k.
Federated learning with differential privacy: Algorithms and performance analysis,
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A Tight Context-aware Privacy Bound for Histogram Publication
For histograms whose bins each have probability at least alpha, Laplace-perturbed counts leak at most 2/b - log(1 - alpha + alpha e^(2/b)) per record, independent of k.