1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2025
Ten Challenging Problems in Federated Foundation Models
Tao Fan, Hanlin Gu, Xuemei Cao +30
Federated Foundation Models (FedFMs) represent a distributed learning paradigm that fuses general competences of foundation models as well as privacy-preserving capabilities of fed…
cs.LG2021★ 1 cited
H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning
He Yang
The longstanding goals of federated learning (FL) require rigorous privacy guarantees and low communication overhead while holding a relatively high model accuracy. However, simult…