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Communication-Efficient Federated Learning with Accelerated Client
  Gradient

Communication-Efficient Federated Learning with Accelerated Client Gradient

10 January 2022
Geeho Kim
Jinkyu Kim
Bohyung Han
    FedML
ArXivPDFHTML

Papers citing "Communication-Efficient Federated Learning with Accelerated Client Gradient"

11 / 11 papers shown
Title
TACO: Tackling Over-correction in Federated Learning with Tailored Adaptive Correction
TACO: Tackling Over-correction in Federated Learning with Tailored Adaptive Correction
Weijie Liu
Ziwei Zhan
Carlee Joe-Wong
Edith Ngai
Jingpu Duan
Deke Guo
Xu Chen
X. Zhang
FedML
53
0
0
24 Apr 2025
Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation
Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation
Siladittya Manna
Suresh Das
Sayantari Ghosh
Saumik Bhattacharya
FedML
43
0
0
30 Mar 2025
Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning
Jisoo Kim
Sungmin Kang
Sunwoo Lee
FedML
42
0
0
14 Mar 2025
Neighborhood and Global Perturbations Supported SAM in Federated
  Learning: From Local Tweaks To Global Awareness
Neighborhood and Global Perturbations Supported SAM in Federated Learning: From Local Tweaks To Global Awareness
Boyuan Li
Zihao Peng
Yafei Li
Mingliang Xu
Shengbo Chen
Baofeng Ji
Cong Shen
FedML
58
0
0
26 Aug 2024
Relaxed Contrastive Learning for Federated Learning
Relaxed Contrastive Learning for Federated Learning
Seonguk Seo
Jinkyu Kim
Geeho Kim
Bohyung Han
FedML
42
8
0
10 Jan 2024
Adaptive Self-Distillation for Minimizing Client Drift in Heterogeneous
  Federated Learning
Adaptive Self-Distillation for Minimizing Client Drift in Heterogeneous Federated Learning
M.Yashwanth
Gaurav Kumar Nayak
Aryaveer Singh
Yogesh Singh
Anirban Chakraborty
FedML
22
1
0
31 May 2023
Towards Understanding and Mitigating Dimensional Collapse in
  Heterogeneous Federated Learning
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning
Yujun Shi
Jian Liang
Wenqing Zhang
Vincent Y. F. Tan
Song Bai
FedML
79
55
0
01 Oct 2022
FedProc: Prototypical Contrastive Federated Learning on Non-IID data
FedProc: Prototypical Contrastive Federated Learning on Non-IID data
Xutong Mu
Yulong Shen
Ke Cheng
Xueli Geng
Jiaxuan Fu
Tao Zhang
Zhiwei Zhang
FedML
35
161
0
25 Sep 2021
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
760
0
28 Sep 2019
Adaptive Federated Learning in Resource Constrained Edge Computing
  Systems
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
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
281
11,677
0
09 Mar 2017
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