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Adaptive Federated Dropout: Improving Communication Efficiency and
  Generalization for Federated Learning

Adaptive Federated Dropout: Improving Communication Efficiency and Generalization for Federated Learning

8 November 2020
Nader Bouacida
Jiahui Hou
H. Zang
Xin Liu
    FedML
ArXivPDFHTML

Papers citing "Adaptive Federated Dropout: Improving Communication Efficiency and Generalization for Federated Learning"

13 / 13 papers shown
Title
Clustering-Based Evolutionary Federated Multiobjective Optimization and Learning
Clustering-Based Evolutionary Federated Multiobjective Optimization and Learning
Chengui Xiao
Songbai Liu
FedML
72
0
0
29 Apr 2025
FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning
FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning
Nurbek Tastan
Samuel Horváth
Martin Takáč
Karthik Nandakumar
FedML
57
0
0
03 Oct 2024
Personalized federated learning based on feature fusion
Personalized federated learning based on feature fusion
Wolong Xing
Zhenkui Shi
Hongyan Peng
Xiantao Hu
Xianxian Li
FedML
33
0
0
24 Jun 2024
FedDD: Toward Communication-efficient Federated Learning with
  Differential Parameter Dropout
FedDD: Toward Communication-efficient Federated Learning with Differential Parameter Dropout
Zhiying Feng
Xu Chen
Qiong Wu
Wenhua Wu
Xiaoxi Zhang
Qian Huang
FedML
33
2
0
31 Aug 2023
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated
  Learning with Bayesian Inference-Based Adaptive Dropout
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated Learning with Bayesian Inference-Based Adaptive Dropout
Jingjing Xue
Min Liu
Sheng Sun
Yuwei Wang
Hui Jiang
Xue Jiang
18
7
0
14 Jul 2023
Towards Fair Federated Recommendation Learning: Characterizing the
  Inter-Dependence of System and Data Heterogeneity
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity
Kiwan Maeng
Haiyu Lu
Luca Melis
John Nguyen
Michael G. Rabbat
Carole-Jean Wu
FedML
29
31
0
30 May 2022
Fast Server Learning Rate Tuning for Coded Federated Dropout
Fast Server Learning Rate Tuning for Coded Federated Dropout
Giacomo Verardo
Daniela F. Barreira
Marco Chiesa
Dejan Kostić
Gerald Q. Maguire Jr
FedML
27
1
0
26 Jan 2022
FedDropoutAvg: Generalizable federated learning for histopathology image
  classification
FedDropoutAvg: Generalizable federated learning for histopathology image classification
G. N. Gunesli
M. Bilal
S. Raza
Nasir M. Rajpoot
FedML
OOD
17
20
0
25 Nov 2021
Towards Fairness-Aware Federated Learning
Towards Fairness-Aware Federated Learning
Yuxin Shi
Han Yu
Cyril Leung
FedML
21
79
0
02 Nov 2021
DAdaQuant: Doubly-adaptive quantization for communication-efficient
  Federated Learning
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning
Robert Hönig
Yiren Zhao
Robert D. Mullins
FedML
107
53
0
31 Oct 2021
Enabling On-Device Training of Speech Recognition Models with Federated
  Dropout
Enabling On-Device Training of Speech Recognition Models with Federated Dropout
Dhruv Guliani
Lillian Zhou
Changwan Ryu
Tien-Ju Yang
Harry Zhang
Yong Xiao
F. Beaufays
Giovanni Motta
FedML
24
16
0
07 Oct 2021
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training
Chen Dun
Cameron R. Wolfe
C. Jermaine
Anastasios Kyrillidis
16
21
0
02 Jul 2021
Communication-Efficient Federated Learning with Dual-Side Low-Rank
  Compression
Communication-Efficient Federated Learning with Dual-Side Low-Rank Compression
Zhefeng Qiao
Xianghao Yu
Jun Zhang
Khaled B. Letaief
FedML
33
19
0
26 Apr 2021
1