Differentially Private Frequency Moments Estimation with Polylogarithmic Space
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We prove that 𝔽_p sketch, a well-celebrated streaming algorithm for frequency moments estimation, is differentially private as is. 𝔽_p sketch uses only polylogarithmic space, exponentially better than existing DP baselines and only worse than the optimal non-private baseline by a logarithmic factor. The evaluation shows that 𝔽_p sketch can achieve reasonable accuracy with strong privacy guarantees.
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