937 citations · 3.8k across the 80 of their papers we have counts for
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cs.LG2021★ 2 cited
Adapting to Function Difficulty and Growth Conditions in Private Optimization
Hilal Asi, Daniel Levy, John Duchi
We develop algorithms for private stochastic convex optimization that adapt to the hardness of the specific function we wish to optimize. While previous work provide worst-case bou…
cs.LG2021★ 2 cited
Federated Asymptotics: a model to compare federated learning algorithms
Gary Cheng, Karan Chadha, John Duchi
We propose an asymptotic framework to analyze the performance of (personalized) federated learning algorithms. In this new framework, we formulate federated learning as a multi-cri…
cs.LG2021★ 12 cited
Private Adaptive Gradient Methods for Convex Optimization
Hilal Asi, John Duchi, Alireza Fallah +2
We study adaptive methods for differentially private convex optimization, proposing and analyzing differentially private variants of a Stochastic Gradient Descent (SGD) algorithm w…