Search Results for author: Omid Javidbakht

Found 3 papers, 0 papers with code

Private Adaptive Gradient Methods for Convex Optimization

no code implementations25 Jun 2021 Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar

We study adaptive methods for differentially private convex optimization, proposing and analyzing differentially private variants of a Stochastic Gradient Descent (SGD) algorithm with adaptive stepsizes, as well as the AdaGrad algorithm.

Element Level Differential Privacy: The Right Granularity of Privacy

no code implementations5 Dec 2019 Hilal Asi, John Duchi, Omid Javidbakht

Differential Privacy (DP) provides strong guarantees on the risk of compromising a user's data in statistical learning applications, though these strong protections make learning challenging and may be too stringent for some use cases.

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