2 papers
cs.DC2025
Convergence Analysis of Split Federated Learning on Heterogeneous Data
Pengchao Han, Chao Huang, Geng Tian +2
Split federated learning (SFL) is a recent distributed approach for collaborative model training among multiple clients. In SFL, a global model is typically split into two parts, w…
cs.DC2024
The Impact of Cut Layer Selection in Split Federated Learning
Justin Dachille, Chao Huang, Xin Liu
Split Federated Learning (SFL) is a distributed machine learning paradigm that combines federated learning and split learning. In SFL, a neural network is partitioned at a cut laye…