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Author

Ryan McKenna

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#machine learning Jan 2026

DP-λCGD: Efficient Noise Correlation for Differentially Private Model Training

This work proposes a new algorithm for correlated-noise private training that correlates noise only with the immediately preceding iteration and cancels a tunable portion of it and shows that the computational overhead is minimal and improved accuracy over DP-SGD is demonstrated.

Nikita P. Kalinin, Ryan McKenna, Rasmus Pagh et al. · 3 citations

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