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cs.LG2026
DP-λCGD: Efficient Noise Correlation for Differentially Private Model Training
Nikita P. Kalinin, Ryan McKenna, Rasmus Pagh +1
Differentially private stochastic gradient descent (DP-SGD) is the gold standard for training machine learning models with formal differential privacy guarantees. Several recent ex…
cs.LG2024
Streaming Private Continual Counting via Binning
Joel Daniel Andersson, Rasmus Pagh
In differential privacy, refers to problems in which we wish to continuously release a function of a dataset that is revealed one element at a time…