Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx

14 December 2023

Papers citing "Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx"

8 / 8 papers shown

Title
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework Zilinghan Li Shilan He Ze Yang Minseok Ryu Kibaek Kim Ravi K. Madduri FedML 60 6 0 17 Sep 2024
Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources -- A Case Study on Federated Fine-tuning of LLaMA 2 Zilinghan Li Shilan He Pranshu Chaturvedi Volodymyr V. Kindratenko Eliu A. Huerta Kibaek Kim Ravi K. Madduri FedML 18 3 0 19 Feb 2024
FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications Grant Wilkins Sheng Di Jon C. Calhoun Zilinghan Li Kibaek Kim Robert Underwood Richard Mortier Franck Cappello FedML 45 2 0 20 Dec 2023
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler Zilinghan Li Pranshu Chaturvedi Shilan He Han-qiu Chen Gagandeep Singh Volodymyr V. Kindratenko Eliu A. Huerta Kibaek Kim Ravi K. Madduri FedML 42 9 0 26 Sep 2023
Test-Time Robust Personalization for Federated Learning Liang Jiang Tao R. Lin FedML OOD TTA 82 43 0 22 May 2022
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 209 841 0 01 Mar 2021
funcX: A Federated Function Serving Fabric for Science Ryan Chard Y. Babuji Zhuozhao Li Tyler J. Skluzacek A. Woodard Ben Blaiszik Ian Foster Kyle Chard 44 187 0 07 May 2020
Survey of Personalization Techniques for Federated Learning V. Kulkarni Milind Kulkarni Aniruddha Pant FedML 182 326 0 19 Mar 2020