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January 14, 20260 citationsOpen Access

Two-Term Asymptotic Expansion of Jensen–Shannon Leakage for Subsampled Gaussian Sum Release

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ASAlex B. Shvets

Key Points

  • This research aims to explore the asymptotic behavior of Jensen–Shannon leakage in subsampled Gaussian sum release.
  • Analytical approach focusing on subsampling at rate q among n users.
  • Used a Gaussian mixture model with noise variance sigma^2 to derive results.
  • Proved the relationship involving JSD, SNR, and n.
  • Established that JSD(P0,P1) follows a specific asymptotic form as n increases.
  • The remainder term shows a uniform behavior across certain parameters.
  • Numerical quadrature confirmed the theoretical asymptotic behavior.

Abstract

We consider subsampling at rate q among n users and a Gaussian sum-release with noise variance sigma². For neighboring datasets D0= (0,. . . , 0) and D1= (mu, 0,. . . , 0), letting SNR=mu²/sigma², we prove JSD (P0, P1) = (q*SNR) / (8n) + ( (4-12q+7q²) /64) * (SNR²/n²) + O (n^-3). The remainder is uniform for q in eps, 1 (any fixed eps>0) and bounded SNR. The proof combines an exact mixture representation, a local Edgeworth expansion, uniform sixth-derivative control, and a parity argument. Numerical quadrature of the exact binomial–Gaussian mixture corroborates the uniform n^-3 behavior.

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Cite This Study

Alex B. Shvets (2026) studied this question.

synapsesocial.com/papers/6966e71813bf7a6f02bff64ehttps://doi.org/10.5281/zenodo.18212281
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