2 papers
cs.DC2026
Privacy-preserving Chunk Scheduling in a BitTorrent Implementation of Federated Learning
Naicheng Li, Javad Dogani, Rui Wang +2
Traditional federated learning (FL) relies on a central aggregator server, which can create performance bottlenecks and privacy risks. Decentralized mix-and-forward designs remove…
cs.CR2024
FedQV: Leveraging Quadratic Voting in Federated Learning
Tianyue Chu, Nikolaos Laoutaris
Federated Learning (FL) permits different parties to collaboratively train a global model without disclosing their respective local labels. A crucial step of FL, that of aggregatin…