DISTREAL: Distributed Resource-Aware Learning in Heterogeneous Systems

16 December 2021

Papers citing "DISTREAL: Distributed Resource-Aware Learning in Heterogeneous Systems"

7 / 7 papers shown

Title
Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous Models Y. Cai Ziqi Zhang Ding Li Yao Guo Xiangqun Chen 41 0 0 13 Mar 2025
EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control Xiaocheng Li Si-ren Liu Zimu Zhou Bin Guo Yuan Xu Zhiwen Yu 10 0 0 29 Jan 2024
Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices Kilian Pfeiffer R. Khalili J. Henkel FedML 31 5 0 26 May 2023
FedZero: Leveraging Renewable Excess Energy in Federated Learning Philipp Wiesner R. Khalili Dennis Grinwald Pratik Agrawal L. Thamsen O. Kao 11 14 0 24 May 2023
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 165 267 0 26 Feb 2021
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 948 20,214 0 17 Apr 2017
Runtime Configurable Deep Neural Networks for Energy-Accuracy Trade-off Hokchhay Tann S. Hashemi R. I. Bahar Sherief Reda 16 72 0 19 Jul 2016