To Talk or to Work: Flexible Communication Compression for Energy
Efficient Federated Learning over Heterogeneous Mobile Edge Devices

To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices

22 December 2020

Papers citing "To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices"

18 / 18 papers shown

Title
FedEx: Expediting Federated Learning over Heterogeneous Mobile Devices by Overlapping and Participant Selection Jiaxiang Geng Boyu Li Xiaoqi Qin Yixuan Li Liang Li Yanzhao Hou Miao Pan FedML 38 0 0 01 Jul 2024
Towards Energy-Aware Federated Learning via MARL: A Dual-Selection Approach for Model and Client Jun Xia Yi Zhang Yiyu Shi 29 0 0 13 May 2024
WHALE-FL: Wireless and Heterogeneity Aware Latency Efficient Federated Learning over Mobile Devices via Adaptive Subnetwork Scheduling Huai-an Su Jiaxiang Geng Liang Li Xiaoqi Qin Yanzhao Hou Xin Fu Miao Pan Miao Pan 40 1 0 01 May 2024
Fed-CVLC: Compressing Federated Learning Communications with Variable-Length Codes Xiaoxin Su Yipeng Zhou Laizhong Cui John C. S. Lui Jiangchuan Liu FedML 27 1 0 06 Feb 2024
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices Peichun Li Guoliang Cheng Xumin Huang Jiawen Kang Rong Yu Yuan Wu Miao Pan FedML 42 21 0 08 Jan 2023
Federated Learning with Flexible Control Shiqiang Wang Jake B. Perazzone Mingyue Ji Kevin S. Chan FedML 28 17 0 16 Dec 2022
Communication-Efficient Federated Learning for Heterogeneous Edge Devices Based on Adaptive Gradient Quantization Heting Liu Fang He Guohong Cao FedML MQ 16 24 0 16 Dec 2022
Joint Optimization of Energy Consumption and Completion Time in Federated Learning Xinyu Zhou Jun Zhao Huimei Han C. Guet FedML 43 27 0 29 Sep 2022
Energy Efficient Deployment and Orchestration of Computing Resources at the Network Edge: a Survey on Algorithms, Trends and Open Challenges N. Shalavi Giovanni Perin Andrea Zanella M. Rossi 16 6 0 28 Sep 2022
Scheduling Algorithms for Federated Learning with Minimal Energy Consumption L. Pilla 14 15 0 13 Sep 2022
A Fast Blockchain-based Federated Learning Framework with Compressed Communications Laizhong Cui Xiaoxin Su Yipeng Zhou FedML 8 23 0 12 Aug 2022
Combined Federated and Split Learning in Edge Computing for Ubiquitous Intelligence in Internet of Things: State of the Art and Future Directions Qiang Duan Shijing Hu Ruijun Deng Zhihui Lu FedML 23 61 0 20 Jul 2022
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity Kiwan Maeng Haiyu Lu Luca Melis John Nguyen Michael G. Rabbat Carole-Jean Wu FedML 29 31 0 30 May 2022
Towards Communication-Learning Trade-off for Federated Learning at the Network Edge Jian-ji Ren Wanli Ni Hui Tian FedML 15 15 0 27 May 2022
To Talk or to Work: Delay Efficient Federated Learning over Mobile Edge Devices Pavana Prakash Jiahao Ding Maoqiang Wu Minglei Shu Rong Yu M. Pan FedML 35 3 0 01 Nov 2021
Management of Resource at the Network Edge for Federated Learning Silvana Trindade L. Bittencourt N. Fonseca 16 6 0 07 Jul 2021
Towards Energy Efficient Federated Learning over 5G+ Mobile Devices Dian Shi Liang Li Rui Chen Pavana Prakash M. Pan Yuguang Fang 33 44 0 13 Jan 2021
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 144 1,685 0 14 Apr 2018