FL-MAC-RDP: federated learning over multiple access channels with Rényi differential privacy

DOI10.1007/S10773-021-04867-0OpenAlexW3184528416MaRDI QIDQ2239648

Mengqing Yu, Yuan-Hong Tao, Moushira Abdallah Mohamed Ahmed, Yaguan Qian, Shu-Hui Wu

Publication date: 5 November 2021

Published in: International Journal of Theoretical Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10773-021-04867-0

zbMATH Keywords

federated learningmultiple access channelsquantization stochastic gradient descentRényi differential privacy

Mathematics Subject Classification ID

Theory of data (68Pxx) Communication, information (94Axx)

Uses Software

• JStatCom
• PrivateLR

Cites Work

• Rényi Divergence and Kullback-Leibler Divergence
• Advances and Open Problems in Federated Learning
• High-Dimensional Stochastic Gradient Quantization for Communication-Efficient Edge Learning
• Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air
• On Analog Gradient Descent Learning Over Multiple Access Fading Channels
• Differential Privacy

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