Private stochastic convex optimization: optimal rates in linear time

DOI10.1145/3357713.3384335OpenAlexW3034801477MaRDI QIDQ5144932

Kunal Talwar, Vitaly Feldman, Tomer Koren

Publication date: 19 January 2021

Published in: Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2005.04763

zbMATH Keywords

stochastic gradient descentdifferential privacystochastic convex optimization

Mathematics Subject Classification ID

Theory of computing (68Qxx)

Related Items (7)

Differentially private SGD with non-smooth losses ⋮ Optimal algorithms for differentially private stochastic monotone variational inequalities and saddle-point problems ⋮ Communication-efficient and privacy-preserving large-scale federated learning counteracting heterogeneity ⋮ PAC privacy: automatic privacy measurement and control of data processing ⋮ Differentially private inference via noisy optimization ⋮ Gradient complexity and non-stationary views of differentially private empirical risk minimization ⋮ Learning privately with labeled and unlabeled examples

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