2 papers
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…
cs.LG2024
FedUV: Uniformity and Variance for Heterogeneous Federated Learning
Ha Min Son, Moon-Hyun Kim, Tai-Myoung Chung +2
Federated learning is a promising framework to train neural networks with widely distributed data. However, performance degrades heavily with heterogeneously distributed data. Rece…