Tackling System and Statistical Heterogeneity for Federated Learning
with Adaptive Client Sampling

Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling

21 December 2021

Leandros Tassiulas

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Papers citing "Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling"

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Title
Federated Learning with Regularized Client Participation Grigory Malinovsky Samuel Horváth Konstantin Burlachenko Peter Richtárik FedML 113 15 0 07 Feb 2023
Adaptive Control of Client Selection and Gradient Compression for Efficient Federated Learning Zhida Jiang Yang Xu Hong-Ze Xu Zhiyuan Wang Chen Qian 75 9 0 19 Dec 2022
Federated Learning with Flexible Control Maroun Touma Jake B. Perazzone Mingyue Ji Kevin S. Chan FedML 106 19 0 16 Dec 2022
Scheduling and Aggregation Design for Asynchronous Federated Learning over Wireless Networks Chung-Hsuan Hu Zheng Chen Erik G. Larsson 102 80 0 14 Dec 2022
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning Shiqi He Qifan Yan Feijie Wu Lanjun Wang Mathias Lécuyer Ivan Beschastnikh FedML 118 10 0 03 Dec 2022
Flow: Per-Instance Personalized Federated Learning Through Dynamic Routing Kunjal Panchal Sunav Choudhary Nisarg Parikh Lijun Zhang Hui Guan 158 6 0 28 Nov 2022
Client Selection in Federated Learning: Principles, Challenges, and Opportunities Lei Fu Huan Zhang Ge Gao Mi Zhang Xin Liu FedML 123 163 0 03 Nov 2022
GradSkip: Communication-Accelerated Local Gradient Methods with Better Computational Complexity Artavazd Maranjyan M. Safaryan Peter Richtárik 150 13 0 28 Oct 2022
Depersonalized Federated Learning: Tackling Statistical Heterogeneity by Alternating Stochastic Gradient Descent Yujie Zhou Zhidu Li Tong Tang Ruyang Wang FedML 102 0 0 07 Oct 2022
A Survey on Participant Selection for Federated Learning in Mobile Networks Behnaz Soltani Venus Haghighi A. Mahmood Quan.Z Sheng Lina Yao FedML 142 29 0 08 Jul 2022
DELTA: Diverse Client Sampling for Fasting Federated Learning Lung-Chuang Wang Yongxin Guo Tao R. Lin Xiaoying Tang FedML 182 30 0 27 May 2022
Optimal Client Sampling for Federated Learning Jiajun He Samuel Horváth Peter Richtárik FedML 175 211 0 26 Oct 2020