Fine-Grained Data Selection for Improved Energy Efficiency of Federated Edge Learning

20 June 2021

Papers citing "Fine-Grained Data Selection for Improved Energy Efficiency of Federated Edge Learning"

8 / 8 papers shown

Title
Efficient Data Labeling and Optimal Device Scheduling in HWNs Using Clustered Federated Semi-Supervised Learning Moqbel Hamood A. Albaseer M. Abdallah Ala I. Al-Fuqaha 69 0 0 22 Dec 2024
A Comprehensive Survey on Joint Resource Allocation Strategies in Federated Edge Learning Jingbo Zhang Qiong Wu Pingyi Fan Q. Fan FedML 28 0 0 10 Oct 2024
Energy-Efficient Federated Edge Learning with Streaming Data: A Lyapunov Optimization Approach Chung-Hsuan Hu Zheng Chen Erik G. Larsson 31 2 0 20 May 2024
Green Edge AI: A Contemporary Survey Yuyi Mao X. Yu Kaibin Huang Ying-Jun Angela Zhang Jun Zhang 28 17 0 01 Dec 2023
Dynamic Scheduling for Federated Edge Learning with Streaming Data Chung-Hsuan Hu Zheng Chen Erik G. Larsson 24 4 0 02 May 2023
Exploration and Exploitation in Federated Learning to Exclude Clients with Poisoned Data Shadha Tabatabai Ihab Mohammed Basheer Qolomany A. Albaseer Kashif Ahmad M. Abdallah Ala I. Al-Fuqaha FedML 13 3 0 29 Apr 2022
Client Selection Approach in Support of Clustered Federated Learning over Wireless Edge Networks A. Albaseer M. Abdallah Ala I. Al-Fuqaha A. Erbad 14 32 0 16 Aug 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