Federated learning and privacy-Reference-Cited by-同舟云学术

Federated learning and privacy

Published:2022-03-19 Issue:4 Volume:65 Page:90-97
ISSN:0001-0782
Container-title:Communications of the ACM
language:en
Short-container-title:Commun. ACM

Author:

Bonawitz Kallista¹,Kairouz Peter¹,Mcmahan Brendan¹,Ramage Daniel¹

Affiliation:

1. Google

Abstract

Building privacy-preserving systems for machine learning and data science on decentralized data.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Link

https://dl.acm.org/doi/pdf/10.1145/3500240

Reference19 articles.

1. Deep Learning with Differential Privacy

2. Balle , B. , Kairouz , P. , McMahan , H.B. , Thakkar , O. , Thakurta , A. Privacy amplification via random check-ins. arXiv , 2020 ; https://arxiv.org/pdf/2007.06605.pdf. Balle, B., Kairouz, P., McMahan, H.B., Thakkar, O., Thakurta, A. Privacy amplification via random check-ins. arXiv, 2020; https://arxiv.org/pdf/2007.06605.pdf.

3. Secure Single-Server Aggregation with (Poly)Logarithmic Overhead

4. Prochlo

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