Provable Privacy Advantages of Decentralized Federated Learning via
Distributed Optimization

Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization

12 July 2024

Milan Lopuhaä-Zwakenberg

Mads Græsbøll Christensen

Richard Heusdens

Papers citing "Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization"

5 / 5 papers shown

Title
From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges Qiongxiu Li Wenrui Yu Yufei Xia Jun Pang FedML 50 1 0 10 Mar 2025
Re-Evaluating Privacy in Centralized and Decentralized Learning: An Information-Theoretical and Empirical Study Changlong Ji Stephane Maag Richard Heusdens Qiongxiu Li FedML 24 2 0 21 Sep 2024
Swarm Learning: A Survey of Concepts, Applications, and Trends Elham Shammar Xiaohui Cui M. A. Al-qaness 26 2 0 01 May 2024
On the (In)security of Peer-to-Peer Decentralized Machine Learning Dario Pasquini Mathilde Raynal Carmela Troncoso OOD FedML 35 19 0 17 May 2022
When the Curious Abandon Honesty: Federated Learning Is Not Private Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML AAML 69 181 0 06 Dec 2021