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FLARE: A New Federated Learning Framework with Adjustable Learning Rates
  over Resource-Constrained Wireless Networks

FLARE: A New Federated Learning Framework with Adjustable Learning Rates over Resource-Constrained Wireless Networks

23 April 2024
Bingnan Xiao
Jingjing Zhang
Wei Ni
Xin Eric Wang
ArXivPDFHTML

Papers citing "FLARE: A New Federated Learning Framework with Adjustable Learning Rates over Resource-Constrained Wireless Networks"

4 / 4 papers shown
Title
Cost-Effective Federated Learning in Mobile Edge Networks
Cost-Effective Federated Learning in Mobile Edge Networks
Bing Luo
Xiang Li
Shiqiang Wang
Jianwei Huang
Leandros Tassiulas
FedML
42
71
0
12 Sep 2021
Linear Convergence in Federated Learning: Tackling Client Heterogeneity
  and Sparse Gradients
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
Convergence of Update Aware Device Scheduling for Federated Learning at
  the Wireless Edge
Convergence of Update Aware Device Scheduling for Federated Learning at the Wireless Edge
M. Amiri
Deniz Gunduz
Sanjeev R. Kulkarni
H. Vincent Poor
63
168
0
28 Jan 2020
FedPAQ: A Communication-Efficient Federated Learning Method with
  Periodic Averaging and Quantization
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
Amirhossein Reisizadeh
Aryan Mokhtari
Hamed Hassani
Ali Jadbabaie
Ramtin Pedarsani
FedML
157
756
0
28 Sep 2019
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