Differentially private stochastic gradient descent

Differentially private stochastic gradient descent (DP-SGD) is an algorithmic technique for learning and a refined analysis of privacy costs within the framework of differential privacy. DP-SGD was introduced by Abadi et al.

Source: Wikipedia — Differentially private stochastic gradient descent (CC BY-SA 4.0)

Differentially private stochastic gradient descent

Differentially private stochastic gradient descent (DP-SGD) is an algorithmic technique for learning and a refined analysis of privacy costs within the framework of differential privacy. DP-SGD was introduced by Abadi et al.

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Source: Wikipedia "Differentially private stochastic gradient descent" · CC BY-SA 4.0

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