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Tagged with differential-privacy gaussian-noise
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Introducing differential privacy in two different ways
I would like to investigate if it is possible to introduce Differential Privacy (DP) to a model via both adding Laplacian noise to the training data and then training with DP-SGD updates. Is it a ...
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Differential privacy guarantees of Gaussian noise, when each coordinate has different sensitivity
Suppose you have a function $f$ that takes a dataset $D$ as input and returns an output in $\mathbb{R}^d$.
If this function has $L^2$-sensitivity $\Delta$, then the analytical Gaussian mechanism (...
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