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A Smooth Binary Mechanism for Efficient Private Continual Observation

NeurIPS 2023 · Optimization › Nonconvex and smooth optimization · approach: Variance-reduced policy gradient · 2 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use only balanced-binary-representation leaves (smooth binary mechanism) instead of all leavesBinary mechanism · Continual countingnormalized variance: $1$ -> $0.25 + o(1)$Helped
Smooth binary vs binary mechanism at T=250 last stepBinary mechanism · Continual countingvariance: 3.27Helped
Use smooth binary mechanism with stable errorBinary mechanism · Continual countingerror distribution across timeHelped
Use matrix factorization mechanism instead of smooth binarySmooth Binary Mechanism · Continual countingvariance: $0.25 + o(1)$ -> $0.0487\hdots + o(1)$Helped
Use smooth binary mechanism instead of factorization mechanismFactorization mechanism · Continual counting, d=10^4time and space: $O(T^2)$ -> $O(\log{T})$Helped
Smooth binary vs binary mechanism noise generationBinary mechanism · Continual countingcomputation timeHurt
Honaker Online vs binary mechanismBinary mechanism · Continual countingvariance: $1$ -> $0.5 + o(1)$Helped

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