Topology-aware Federated Learning in Edge Computing: A Comprehensive
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Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey

6 February 2023

Papers citing "Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey"

9 / 9 papers shown

Title
Hubs and Spokes Learning: Efficient and Scalable Collaborative Machine Learning Atul Sharma Kavindu Herath Saurabh Bagchi Chaoyue Liu Somali Chaterji FedML 37 0 0 29 Apr 2025
Efficient Personalized Federated Learning via Sparse Model-Adaptation Daoyuan Chen Fandong Meng Dawei Gao Bolin Ding Yaliang Li FedML 96 45 0 04 May 2023
Federated Learning Challenges and Opportunities: An Outlook Jie Ding Eric W. Tramel Anit Kumar Sahu Shuang Wu Salman Avestimehr Tao Zhang FedML 23 53 0 01 Feb 2022
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 180 832 0 01 Mar 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 168 267 0 26 Feb 2021
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation Su Wang Mengyuan Lee Seyyedali Hosseinalipour Roberto Morabito M. Chiang Christopher G. Brinton FedML 77 108 0 04 Jan 2021
Throughput-Optimal Topology Design for Cross-Silo Federated Learning Othmane Marfoq Chuan Xu Giovanni Neglia Richard Vidal FedML 43 85 0 23 Oct 2020
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 174 1,690 0 18 Mar 2020
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 157 756 0 28 Sep 2019