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Adaptive Gradient Sparsification for Efficient Federated Learning: An
  Online Learning Approach

Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach

14 January 2020
Pengchao Han
Shiqiang Wang
K. Leung
    FedML
ArXivPDFHTML

Papers citing "Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach"

44 / 44 papers shown
Title
DaringFed: A Dynamic Bayesian Persuasion Pricing for Online Federated Learning under Two-sided Incomplete Information
DaringFed: A Dynamic Bayesian Persuasion Pricing for Online Federated Learning under Two-sided Incomplete Information
Yun Xin
Jianfeng Lu
Shuqin Cao
Gang Li
Haozhao Wang
Guanghui Wen
FedML
19
0
0
09 May 2025
Sparsification Under Siege: Defending Against Poisoning Attacks in Communication-Efficient Federated Learning
Sparsification Under Siege: Defending Against Poisoning Attacks in Communication-Efficient Federated Learning
Zhiyong Jin
Runhua Xu
Chong Li
Y. Liu
Jianxin Li
AAML
FedML
39
0
0
30 Apr 2025
Soft-Label Caching and Sharpening for Communication-Efficient Federated Distillation
Soft-Label Caching and Sharpening for Communication-Efficient Federated Distillation
Kitsuya Azuma
Takayuki Nishio
Yuichi Kitagawa
Wakako Nakano
Takahito Tanimura
FedML
70
0
0
28 Apr 2025
Communication-Efficient Device Scheduling for Federated Learning Using Lyapunov Optimization
Jake B. Perazzone
Shiqiang Wang
Mingyue Ji
Kevin S. Chan
FedML
75
0
0
01 Mar 2025
Novel Gradient Sparsification Algorithm via Bayesian Inference
Novel Gradient Sparsification Algorithm via Bayesian Inference
Ali Bereyhi
B. Liang
G. Boudreau
Ali Afana
34
2
0
23 Sep 2024
VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections
VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections
Roy Miles
Pradyumna Reddy
Ismail Elezi
Jiankang Deng
VLM
43
3
0
28 May 2024
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
Zhe Li
Bicheng Ying
Zidong Liu
Haibo Yang
Haibo Yang
FedML
59
3
0
24 May 2024
SignSGD with Federated Voting
SignSGD with Federated Voting
Chanho Park
H. Vincent Poor
Namyoon Lee
FedML
40
1
0
25 Mar 2024
Straggler-resilient Federated Learning: Tackling Computation
  Heterogeneity with Layer-wise Partial Model Training in Mobile Edge Network
Straggler-resilient Federated Learning: Tackling Computation Heterogeneity with Layer-wise Partial Model Training in Mobile Edge Network
Student Member Ieee Hongda Wu
F. I. C. V. Ping Wang
Aswartha Narayana
FedML
49
1
0
16 Nov 2023
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks
Natalie Lang
Nir Shlezinger
Rafael G. L. DÓliveira
S. E. Rouayheb
FedML
75
4
0
01 Aug 2023
A Survey of What to Share in Federated Learning: Perspectives on Model
  Utility, Privacy Leakage, and Communication Efficiency
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency
Jiawei Shao
Zijian Li
Wenqiang Sun
Tailin Zhou
Yuchang Sun
Lumin Liu
Zehong Lin
Yuyi Mao
Jun Zhang
FedML
43
23
0
20 Jul 2023
Information-Theoretically Private Federated Submodel Learning with
  Storage Constrained Databases
Information-Theoretically Private Federated Submodel Learning with Storage Constrained Databases
Sajani Vithana
S. Ulukus
FedML
20
0
0
12 Jul 2023
Complement Sparsification: Low-Overhead Model Pruning for Federated
  Learning
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning
Xiaopeng Jiang
Cristian Borcea
FedML
34
15
0
10 Mar 2023
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous
  Edge Devices
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices
Peichun Li
Guoliang Cheng
Xumin Huang
Jiawen Kang
Rong Yu
Yuan Wu
Miao Pan
FedML
55
21
0
08 Jan 2023
Rate-Privacy-Storage Tradeoff in Federated Learning with Top $r$
  Sparsification
Rate-Privacy-Storage Tradeoff in Federated Learning with Top rrr Sparsification
Sajani Vithana
S. Ulukus
FedML
23
5
0
19 Dec 2022
Federated Learning with Flexible Control
Federated Learning with Flexible Control
Shiqiang Wang
Jake B. Perazzone
Mingyue Ji
Kevin S. Chan
FedML
28
17
0
16 Dec 2022
Communication-Efficient Federated Learning for Heterogeneous Edge
  Devices Based on Adaptive Gradient Quantization
Communication-Efficient Federated Learning for Heterogeneous Edge Devices Based on Adaptive Gradient Quantization
Heting Liu
Fang He
Guohong Cao
FedML
MQ
35
24
0
16 Dec 2022
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth
  Efficient Federated Learning
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
42
7
0
03 Dec 2022
HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics
  in Industrial Metaverse
HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaverse
Shenglai Zeng
Zonghang Li
Hongfang Yu
Zhihao Zhang
Long Luo
Bo-wen Li
Dusit Niyato
34
42
0
07 Nov 2022
A-LAQ: Adaptive Lazily Aggregated Quantized Gradient
A-LAQ: Adaptive Lazily Aggregated Quantized Gradient
Afsaneh Mahmoudi
José Hélio da Cruz Júnior
H. S. Ghadikolaei
Carlo Fischione
34
7
0
31 Oct 2022
Machine Unlearning of Federated Clusters
Machine Unlearning of Federated Clusters
Chao Pan
Jin Sima
Saurav Prakash
Vishal Rana
O. Milenkovic
FedML
MU
39
25
0
28 Oct 2022
Adaptive Top-K in SGD for Communication-Efficient Distributed Learning
Adaptive Top-K in SGD for Communication-Efficient Distributed Learning
Mengzhe Ruan
Guangfeng Yan
Yuanzhang Xiao
Linqi Song
Weitao Xu
40
3
0
24 Oct 2022
Joint Optimization of Energy Consumption and Completion Time in
  Federated Learning
Joint Optimization of Energy Consumption and Completion Time in Federated Learning
Xinyu Zhou
Jun Zhao
Huimei Han
C. Guet
FedML
48
27
0
29 Sep 2022
Private Read Update Write (PRUW) in Federated Submodel Learning (FSL):
  Communication Efficient Schemes With and Without Sparsification
Private Read Update Write (PRUW) in Federated Submodel Learning (FSL): Communication Efficient Schemes With and Without Sparsification
Sajani Vithana
S. Ulukus
FedML
20
19
0
09 Sep 2022
Reducing Impacts of System Heterogeneity in Federated Learning using
  Weight Update Magnitudes
Reducing Impacts of System Heterogeneity in Federated Learning using Weight Update Magnitudes
Irene Wang
32
1
0
30 Aug 2022
Joint Privacy Enhancement and Quantization in Federated Learning
Joint Privacy Enhancement and Quantization in Federated Learning
Natalie Lang
Elad Sofer
Tomer Shaked
Nir Shlezinger
FedML
37
46
0
23 Aug 2022
A Fast Blockchain-based Federated Learning Framework with Compressed
  Communications
A Fast Blockchain-based Federated Learning Framework with Compressed Communications
Laizhong Cui
Xiaoxin Su
Yipeng Zhou
FedML
22
23
0
12 Aug 2022
FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for
  Non-IID Data in Federated Learning
FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning
Nang Hung Nguyen
Phi Le Nguyen
D. Nguyen
Trung Thanh Nguyen
Thuy-Dung Nguyen
H. Pham
Truong Thao Nguyen
FedML
67
24
0
04 Aug 2022
Towards Efficient Communications in Federated Learning: A Contemporary
  Survey
Towards Efficient Communications in Federated Learning: A Contemporary Survey
Zihao Zhao
Yuzhu Mao
Yang Liu
Linqi Song
Ouyang Ye
Xinlei Chen
Wenbo Ding
FedML
54
59
0
02 Aug 2022
Combined Federated and Split Learning in Edge Computing for Ubiquitous
  Intelligence in Internet of Things: State of the Art and Future Directions
Combined Federated and Split Learning in Edge Computing for Ubiquitous Intelligence in Internet of Things: State of the Art and Future Directions
Qiang Duan
Shijing Hu
Ruijun Deng
Zhihui Lu
FedML
31
61
0
20 Jul 2022
Rate Distortion Tradeoff in Private Read Update Write in Federated
  Submodel Learning
Rate Distortion Tradeoff in Private Read Update Write in Federated Submodel Learning
Sajani Vithana
S. Ulukus
FedML
31
8
0
07 Jun 2022
Private Federated Submodel Learning with Sparsification
Private Federated Submodel Learning with Sparsification
Sajani Vithana
S. Ulukus
FedML
26
10
0
31 May 2022
FLAME: Federated Learning Across Multi-device Environments
FLAME: Federated Learning Across Multi-device Environments
Hyunsung Cho
Akhil Mathur
F. Kawsar
16
21
0
17 Feb 2022
On the Convergence of Heterogeneous Federated Learning with Arbitrary
  Adaptive Online Model Pruning
On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning
Hanhan Zhou
Tian-Shing Lan
Guru Venkataramani
Wenbo Ding
FedML
32
6
0
27 Jan 2022
Communication-Efficient Device Scheduling for Federated Learning Using
  Stochastic Optimization
Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization
Jake B. Perazzone
Shiqiang Wang
Mingyue Ji
Kevin S. Chan
FedML
21
72
0
19 Jan 2022
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
57
72
0
12 Sep 2021
A Payload Optimization Method for Federated Recommender Systems
A Payload Optimization Method for Federated Recommender Systems
Farwa K. Khan
Adrian Flanagan
K. E. Tan
Z. Alamgir
Muhammad Ammad-ud-din
82
29
0
27 Jul 2021
Slashing Communication Traffic in Federated Learning by Transmitting
  Clustered Model Updates
Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates
Laizhong Cui
Xiaoxin Su
Yipeng Zhou
Yi Pan
FedML
38
36
0
10 May 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets
  with Ordered Dropout
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
Samuel Horváth
Stefanos Laskaridis
Mario Almeida
Ilias Leondiadis
Stylianos I. Venieris
Nicholas D. Lane
189
268
0
26 Feb 2021
Demystifying Why Local Aggregation Helps: Convergence Analysis of
  Hierarchical SGD
Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD
Jiayi Wang
Shiqiang Wang
Rong-Rong Chen
Mingyue Ji
FedML
36
51
0
24 Oct 2020
SEEC: Semantic Vector Federation across Edge Computing Environments
SEEC: Semantic Vector Federation across Edge Computing Environments
Shalisha Witherspoon
Dean Steuer
Graham A. Bent
N. Desai
FedML
25
2
0
30 Aug 2020
Communication-Efficient and Distributed Learning Over Wireless Networks:
  Principles and Applications
Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications
Jihong Park
S. Samarakoon
Anis Elgabli
Joongheon Kim
M. Bennis
Seong-Lyun Kim
Mérouane Debbah
34
161
0
06 Aug 2020
Model Pruning Enables Efficient Federated Learning on Edge Devices
Model Pruning Enables Efficient Federated Learning on Edge Devices
Yuang Jiang
Shiqiang Wang
Victor Valls
Bongjun Ko
Wei-Han Lee
Kin K. Leung
Leandros Tassiulas
38
444
0
26 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
1,687
0
14 Apr 2018
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