Zhu, R. (author), Yang, M. (author), Wang, Q. (author) Federated Learning (FL) has emerged as a privacy-preserving paradigm for collaborative deep learning model training across distributed data silos. Despite its importance, FL faces challenges such as high latency and less effective global models. In this paper, we propose ShuffleFL, an innovative framework stemming from the hierarchical FL, which...
journal article 2024