2 papers
cs.CR2024
Re-Evaluating Privacy in Centralized and Decentralized Learning: An Information-Theoretical and Empirical Study
Changlong Ji, Stephane Maag, Richard Heusdens +1
Decentralized Federated Learning (DFL) has garnered attention for its robustness and scalability compared to Centralized Federated Learning (CFL). While DFL is commonly believed to…
cs.CR2024
Perfect Gradient Inversion in Federated Learning: A New Paradigm from the Hidden Subset Sum Problem
Qiongxiu Li, Lixia Luo, Agnese Gini +6
Federated Learning (FL) has emerged as a popular paradigm for collaborative learning among multiple parties. It is considered privacy-friendly because local data remains on persona…