Differentially Private Accelerated Optimization Algorithms

5 Aug 2020Nurdan KuruŞ. İlker BirbilMert GurbuzbalabanSinan Yildirim

We present two classes of differentially private optimization algorithms derived from the well-known accelerated first-order methods. The first algorithm is inspired by Polyak's heavy ball method and employs a smoothing approach to decrease the accumulated noise on the gradient steps required for differential privacy... (read more)

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