Author

Nikita P. Kalinin

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#machine learning Jul 2026

Dithered Gaussian Mechanism for Randomness-Efficient Differential Privacy

The dithered Gaussian mechanism is presented, an alternative to the discrete Gaussian mechanism for differential privacy that discretizes the private output rather than the noise distribution itself, and it is shown that cryptographically secure noise generation with reduced exposure to floating-point vulnerabilities c...

Nikita P. Kalinin, Rasmus Pagh · arXiv.org · 1 citation

Jul 2026

Improved Error Bounds for Pure Differentially Private Continual Counting via Matrix Factorization

This work improves the leading constant in the maximum squared error and the mean squared error, and proves an $\Omega(\epsilon^{-2}\log^3 n)$ lower bound for the class of factorizations whose matrices have entries in $\{0,1\}$, matching the upper-bound asymptotics for this class.

P. Arkhipov, Nikita P. Kalinin · arXiv.org · 2 citations · ⚡1