One-Shot Federated Learning for LEO Constellations that Reduces Convergence Time from Days to 90 Minutes

21 May 2023

Papers citing "One-Shot Federated Learning for LEO Constellations that Reduces Convergence Time from Days to 90 Minutes"

10 / 10 papers shown

Title
AsyncFLEO: Asynchronous Federated Learning for LEO Satellite Constellations with High-Altitude Platforms Mohamed Elmahallawy Tie-Mei Luo FedML 48 32 0 22 Dec 2022
FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations Jinhyun So Kevin Hsieh Behnaz Arzani Shadi Noghabi Salman Avestimehr Ranveer Chandra FedML 59 62 0 02 Feb 2022
Ground-Assisted Federated Learning in LEO Satellite Constellations N. Razmi Bho Matthiesen Armin Dekorsy P. Popovski FedML 39 81 0 03 Sep 2021
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li Meirui Jiang Xiaofei Zhang Michael Kamp Qi Dou OOD FedML 278 821 0 15 Feb 2021
Distilled One-Shot Federated Learning Yanlin Zhou George Pu Xiyao Ma Xiaolin Li D. Wu FedML DD 140 161 0 17 Sep 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 259 6,276 0 10 Dec 2019
Dataset Distillation Tongzhou Wang Jun-Yan Zhu Antonio Torralba Alexei A. Efros DD 81 297 0 27 Nov 2018
Wide Residual Networks Sergey Zagoruyko N. Komodakis 351 7,995 0 23 May 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,559 0 17 Feb 2016
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 463 43,328 0 11 Feb 2015