Federated Learning Under Intermittent Client Availability and
Time-Varying Communication Constraints

Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints

13 May 2022

Papers citing "Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints"

16 / 16 papers shown

Title
Debiasing Federated Learning with Correlated Client Participation Zhenyu Sun Ziyang Zhang Zheng Xu Gauri Joshi Pranay Sharma Ermin Wei FedML 29 0 0 02 Oct 2024
Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability Ming Xiang Stratis Ioannidis Edmund Yeh Carlee Joe-Wong Lili Su FedML 37 5 0 26 Sep 2024
Green Federated Learning: A new era of Green Aware AI Dipanwita Thakur Antonella Guzzo Giancarlo Fortino Francesco Piccialli AI4CE 48 4 0 19 Sep 2024
Advances in Robust Federated Learning: A Survey with Heterogeneity Considerations Chuan Chen Tianchi Liao Xiaojun Deng Zihou Wu Sheng Huang Zibin Zheng FedML 44 2 0 16 May 2024
On-Demand Model and Client Deployment in Federated Learning with Deep Reinforcement Learning M. Chahoud Hani Sami Azzam Mourad Hadi Otrok Jamal Bentahar Mohsen Guizani 29 0 0 12 May 2024
FedStale: leveraging stale client updates in federated learning Angelo Rodio Giovanni Neglia FedML 37 4 0 07 May 2024
Towards Fairness in Provably Communication-Efficient Federated Recommender Systems Kirandeep Kaur Sujit Gujar Shweta Jain FedML 48 0 0 03 May 2024
Empowering Federated Learning with Implicit Gossiping: Mitigating Connection Unreliability Amidst Unknown and Arbitrary Dynamics Ming Xiang Stratis Ioannidis Edmund Yeh Carlee Joe-Wong Lili Su FedML 31 2 0 15 Apr 2024
Communication-Efficient Federated Learning for LEO Satellite Networks Integrated with HAPs Using Hybrid NOMA-OFDM Mohamed Elmahallawy Tie-Mei Luo Khaled Ramadan 18 5 0 01 Jan 2024
Federated Learning Under Restricted User Availability Periklis Theodoropoulos Konstantinos E. Nikolakakis Dionysios S. Kalogerias FedML 26 1 0 25 Sep 2023
Collaborative Policy Learning for Dynamic Scheduling Tasks in Cloud-Edge-Terminal IoT Networks Using Federated Reinforcement Learning Do-Yup Kim Dami Lee Ji-Wan Kim Hyun-Suk Lee 31 4 0 02 Jul 2023
MimiC: Combating Client Dropouts in Federated Learning by Mimicking Central Updates Yuchang Sun Yuyi Mao Jinchao Zhang FedML 28 10 0 21 Jun 2023
Federated Learning under Heterogeneous and Correlated Client Availability Angelo Rodio Francescomaria Faticanti Othmane Marfoq Giovanni Neglia Emilio Leonardi FedML 13 27 0 11 Jan 2023
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability Zhilin Wang Xiaoliang Fan Jianzhong Qi Haibing Jin Peizhen Yang Siqi Shen Cheng-i Wang FedML 30 13 0 25 Nov 2022
Client Selection in Federated Learning: Principles, Challenges, and Opportunities Lei Fu Huan Zhang Ge Gao Mi Zhang Xin Liu FedML 34 115 0 03 Nov 2022
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021