GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning

3 December 2022

Papers citing "GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning"

7 / 7 papers shown

Title
FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching Qifan Yan Andrew Liu Shiqi He Mathias Lécuyer Ivan Beschastnikh FedML 36 0 0 21 Apr 2025
FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction Feijie Wu Xingchen Wang Yaqing Wang Tianci Liu Lu Su Jing Gao FedML 45 3 0 28 Jul 2024
Enhancing Neural Training via a Correlated Dynamics Model Jonathan Brokman Roy Betser Rotem Turjeman Tom Berkov I. Cohen Guy Gilboa 24 3 0 20 Dec 2023
Venn: Resource Management for Collaborative Learning Jobs Jiachen Liu Fan Lai Ding Ding Yiwen Zhang Mosharaf Chowdhury FedML 63 1 0 13 Dec 2023
Anchor Sampling for Federated Learning with Partial Client Participation Feijie Wu Song Guo Zhihao Qu Shiqi He Ziming Liu Jing Gao FedML 28 12 0 13 Jun 2022
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients A. Mitra Rayana H. Jaafar George J. Pappas Hamed Hassani FedML 55 157 0 14 Feb 2021
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 174 760 0 28 Sep 2019