Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization

18 March 2022

Papers citing "Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization"

6 / 6 papers shown

Title
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency Jiawei Shao Zijian Li Wenqiang Sun Tailin Zhou Yuchang Sun Lumin Liu Zehong Lin Yuyi Mao Jun Zhang FedML 34 23 0 20 Jul 2023
Heterogeneous Federated Learning: State-of-the-art and Research Challenges Mang Ye Xiuwen Fang Bo Du PongChi Yuen Dacheng Tao FedML AAML 36 244 0 20 Jul 2023
Breaking On-device Training Memory Wall: A Systematic Survey Shitian Li Chunlin Tian Kahou Tam Ruirui Ma Li Li 21 2 0 17 Jun 2023
When Computing Power Network Meets Distributed Machine Learning: An Efficient Federated Split Learning Framework Xinjing Yuan Lingjun Pu Lei Jiao Xiaofei Wang Mei Yang Jingdong Xu FedML 22 4 0 22 May 2023
Personalised Federated Learning On Heterogeneous Feature Spaces A. Rakotomamonjy Maxime Vono H. M. Ruiz L. Ralaivola FedML 18 8 0 26 Jan 2023
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li Meirui Jiang Xiaofei Zhang Michael Kamp Qi Dou OOD FedML 168 787 0 15 Feb 2021