Privacy Amplification by Decentralization

9 December 2020

Papers citing "Privacy Amplification by Decentralization"

8 / 8 papers shown

Title
OledFL: Unleashing the Potential of Decentralized Federated Learning via Opposite Lookahead Enhancement Qinglun Li Miao Zhang Mengzhu Wang Quanjun Yin Li Shen OODD FedML 11 0 0 09 Oct 2024
Straggler-Resilient Differentially-Private Decentralized Learning Yauhen Yakimenka Chung-Wei Weng Hsuan-Yin Lin E. Rosnes J. Kliewer 11 6 0 06 Dec 2022
A principled framework for the design and analysis of token algorithms Hadrien Hendrikx FedML 14 13 0 30 May 2022
Communication-Efficient Triangle Counting under Local Differential Privacy Jacob Imola Takao Murakami Kamalika Chaudhuri 30 30 0 13 Oct 2021
Federated Multi-Task Learning under a Mixture of Distributions Othmane Marfoq Giovanni Neglia A. Bellet Laetitia Kameni Richard Vidal FedML 19 269 0 23 Aug 2021
Throughput-Optimal Topology Design for Cross-Silo Federated Learning Othmane Marfoq Chuan Xu Giovanni Neglia Richard Vidal FedML 43 85 0 23 Oct 2020
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 134 416 0 29 Nov 2018
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 99 570 0 08 Dec 2012