ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1908.07873
  4. Cited By
Federated Learning: Challenges, Methods, and Future Directions

Federated Learning: Challenges, Methods, and Future Directions

IEEE Signal Processing Magazine (IEEE SPM), 2019
21 August 2019
Tian Li
Anit Kumar Sahu
Ameet Talwalkar
Virginia Smith
    FedML
ArXiv (abs)PDFHTML

Papers citing "Federated Learning: Challenges, Methods, and Future Directions"

50 / 1,676 papers shown
Detection of Global Anomalies on Distributed IoT Edges with
  Device-to-Device Communication
Detection of Global Anomalies on Distributed IoT Edges with Device-to-Device Communication
H. Ochiai
Riku Nishihata
Eisuke Tomiyama
Yuwei Sun
Hiroshi Esaki
176
12
0
16 Jul 2024
Novel clustered federated learning based on local loss
Novel clustered federated learning based on local loss
Endong Gu
Yongxin Chen
Hao Wen
Xingju Cai
Deren Han
FedML
221
2
0
12 Jul 2024
Provable Privacy Advantages of Decentralized Federated Learning via
  Distributed Optimization
Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization
Wenrui Yu
Qiongxiu Li
Milan Lopuhaä-Zwakenberg
Mads Græsbøll Christensen
Richard Heusdens
FedML
197
9
0
12 Jul 2024
Combining Federated Learning and Control: A Survey
Combining Federated Learning and Control: A Survey
Jakob Weber
Markus Gurtner
A. Lobe
Adrian Trachte
Andreas Kugi
FedMLAI4CE
338
8
0
12 Jul 2024
Federated Learning and AI Regulation in the European Union: Who is
  Responsible? -- An Interdisciplinary Analysis
Federated Learning and AI Regulation in the European Union: Who is Responsible? -- An Interdisciplinary Analysis
Herbert Woisetschläger
Simon Mertel
Christoph Krönke
R. Mayer
Hans-Arno Jacobsen
FedML
289
4
0
11 Jul 2024
Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in
  the Era of Large Language Models
Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models
Jinliang Lu
Ziliang Pang
Min Xiao
Yaochen Zhu
Rui Xia
Jiajun Zhang
MoMe
412
48
0
08 Jul 2024
Mjolnir: Breaking the Shield of Perturbation-Protected Gradients via Adaptive Diffusion
Mjolnir: Breaking the Shield of Perturbation-Protected Gradients via Adaptive Diffusion
Xuan Liu
Siqi Cai
Qihua Zhou
Song Guo
Ruibin Li
Kaiwei Lin
DiffMAAML
234
0
0
07 Jul 2024
A Joint Approach to Local Updating and Gradient Compression for
  Efficient Asynchronous Federated Learning
A Joint Approach to Local Updating and Gradient Compression for Efficient Asynchronous Federated Learning
Jiajun Song
Jiajun Luo
Rongwei Lu
Shuzhao Xie
Bin Chen
Zhi Wang
FedML
163
2
0
06 Jul 2024
Personalized Federated Domain-Incremental Learning based on Adaptive
  Knowledge Matching
Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching
Yichen Li
Wenchao Xu
Haozhao Wang
Ruixuan Li
Tianzhe Xiao
Jingcai Guo
CLL
270
28
0
06 Jul 2024
Enhancing Federated Learning with Adaptive Differential Privacy and
  Priority-Based Aggregation
Enhancing Federated Learning with Adaptive Differential Privacy and Priority-Based Aggregation
Mahtab Talaei
Iman Izadi
FedML
203
0
0
26 Jun 2024
Differential error feedback for communication-efficient decentralized
  learning
Differential error feedback for communication-efficient decentralized learning
Roula Nassif
Stefan Vlaski
Marco Carpentiero
Vincenzo Matta
Ali H. Sayed
330
3
0
26 Jun 2024
FedAQ: Communication-Efficient Federated Edge Learning via Joint Uplink
  and Downlink Adaptive Quantization
FedAQ: Communication-Efficient Federated Edge Learning via Joint Uplink and Downlink Adaptive Quantization
Linping Qu
Shenghui Song
Chi-Ying Tsui
MQFedML
211
5
0
26 Jun 2024
Federated Dynamical Low-Rank Training with Global Loss Convergence
  Guarantees
Federated Dynamical Low-Rank Training with Global Loss Convergence Guarantees
Steffen Schotthöfer
M. P. Laiu
FedML
246
12
0
25 Jun 2024
Distributed Training of Large Graph Neural Networks with Variable
  Communication Rates
Distributed Training of Large Graph Neural Networks with Variable Communication Rates
J. Cerviño
Md Asadullah Turja
Hesham Mostafa
N. Himayat
Alejandro Ribeiro
GNNAI4CE
342
1
0
25 Jun 2024
Meta-FL: A Novel Meta-Learning Framework for Optimizing Heterogeneous
  Model Aggregation in Federated Learning
Meta-FL: A Novel Meta-Learning Framework for Optimizing Heterogeneous Model Aggregation in Federated Learning
Zahir Alsulaimawi
71
6
0
23 Jun 2024
Embracing Federated Learning: Enabling Weak Client Participation via
  Partial Model Training
Embracing Federated Learning: Enabling Weak Client Participation via Partial Model Training
Sunwoo Lee
Tuo Zhang
Saurav Prakash
Yue Niu
Salman Avestimehr
FedML
230
9
0
21 Jun 2024
SeCTIS: A Framework to Secure CTI Sharing
SeCTIS: A Framework to Secure CTI Sharing
Dincy R. Arikkat
Mert Cihangiroglu
Mauro Conti
Rafidha Rehiman K. A.
S. Nicolazzo
Antonino Nocera
Vinod P
242
9
0
20 Jun 2024
BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison
  Byzantine-robust Federated Learning
BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning
Yi Liu
Cong Wang
Lizhen Qu
AAML
221
5
0
18 Jun 2024
Personalized Federated Knowledge Graph Embedding with Client-Wise
  Relation Graph
Personalized Federated Knowledge Graph Embedding with Client-Wise Relation Graph
Xiaoxiong Zhang
Zhiwei Zeng
Xin Zhou
Dusit Niyato
Zhiqi Shen
FedML
266
6
0
17 Jun 2024
Diffusion Generative Modelling for Divide-and-Conquer MCMC
Diffusion Generative Modelling for Divide-and-Conquer MCMC
C. Trojan
Paul Fearnhead
C. Nemeth
DiffM
202
1
0
17 Jun 2024
Knowledge Distillation in Federated Learning: a Survey on Long Lasting
  Challenges and New Solutions
Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions
Laiqiao Qin
Tianqing Zhu
Wanlei Zhou
Philip S. Yu
230
18
0
16 Jun 2024
H-Fac: Memory-Efficient Optimization with Factorized Hamiltonian Descent
H-Fac: Memory-Efficient Optimization with Factorized Hamiltonian DescentInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Son Nguyen
Lizhang Chen
Bo Liu
Qiang Liu
313
8
0
14 Jun 2024
Federated Learning with Flexible Architectures
Federated Learning with Flexible Architectures
Jong-Ik Park
Carlee Joe-Wong
FedML
276
4
0
14 Jun 2024
Minimizing Energy Costs in Deep Learning Model Training: The Gaussian
  Sampling Approach
Minimizing Energy Costs in Deep Learning Model Training: The Gaussian Sampling Approach
Challapalli Phanindra Revanth
Sumohana S. Channappayya
C Krishna Mohan
245
23
0
11 Jun 2024
Optimal Federated Learning for Nonparametric Regression with
  Heterogeneous Distributed Differential Privacy Constraints
Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints
T. T. Cai
Abhinav Chakraborty
Lasse Vuursteen
FedML
292
8
0
10 Jun 2024
Federated Nonparametric Hypothesis Testing with Differential Privacy
  Constraints: Optimal Rates and Adaptive Tests
Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests
T. T. Cai
Abhinav Chakraborty
Lasse Vuursteen
FedML
286
6
0
10 Jun 2024
Optimisation of federated learning settings under statistical
  heterogeneity variations
Optimisation of federated learning settings under statistical heterogeneity variations
Basem Suleiman
M. J. Alibasa
R. Purwanto
Lewis Jeffries
Ali Anaissi
Jacky Song
FedML
275
0
0
10 Jun 2024
Federated learning in food research
Federated learning in food research
Zuzanna Fendor
Bas H. M. van der Velden
Xinxin Wang
Andrea Jr. Carnoli
Osman Mutlu
Ali Hürriyetoğlu
FedML
169
4
0
10 Jun 2024
Federated Representation Learning in the Under-Parameterized Regime
Federated Representation Learning in the Under-Parameterized RegimeInternational Conference on Machine Learning (ICML), 2024
Renpu Liu
Cong Shen
Jing Yang
356
10
0
07 Jun 2024
Towards Federated Domain Unlearning: Verification Methodologies and
  Challenges
Towards Federated Domain Unlearning: Verification Methodologies and Challenges
Kahou Tam
Kewei Xu
Li Li
Huazhu Fu
MU
275
1
0
05 Jun 2024
Federated Random Forest for Partially Overlapping Clinical Data
Federated Random Forest for Partially Overlapping Clinical Data
Young-Hee Park
Cord Eric Schmidt
Benedikt Marcel Batton
Anne-Christin Hauschild
43
0
0
31 May 2024
subMFL: Compatiple subModel Generation for Federated Learning in Device
  Heterogenous Environment
subMFL: Compatiple subModel Generation for Federated Learning in Device Heterogenous Environment
Zeyneddin Oz
Ceylan Soygul Oz
A. Malekjafarian
Nima Afraz
Fatemeh Golpayegani
FedML
139
1
0
30 May 2024
Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias
  in Federated Semi-Supervised Learning
Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning
Guogang Zhu
Xuefeng Liu
Xinghao Wu
Shaojie Tang
Chao Tang
Jianwei Niu
Hao Su
FedML
347
3
0
30 May 2024
Federated Learning under Partially Class-Disjoint Data via Manifold
  Reshaping
Federated Learning under Partially Class-Disjoint Data via Manifold Reshaping
Ziqing Fan
Jiangchao Yao
Ruipeng Zhang
Lingjuan Lyu
Ya Zhang
Yanfeng Wang
FedML
276
5
0
29 May 2024
Federating Dynamic Models using Early-Exit Architectures for Automatic
  Speech Recognition on Heterogeneous Clients
Federating Dynamic Models using Early-Exit Architectures for Automatic Speech Recognition on Heterogeneous Clients
Mohamed Nabih Ali
Alessio Brutti
Daniele Falavigna
271
1
0
27 May 2024
FedHPL: Efficient Heterogeneous Federated Learning with Prompt Tuning
  and Logit Distillation
FedHPL: Efficient Heterogeneous Federated Learning with Prompt Tuning and Logit Distillation
Yuting Ma
Lechao Cheng
Yaxiong Wang
Zhun Zhong
Xiaohua Xu
Meng Wang
FedML
307
3
0
27 May 2024
Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data
Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data
Xiaolu Wang
Yuchang Sun
Hoi-To Wai
Jun Zhang
282
2
0
27 May 2024
Fair Federated Learning under Domain Skew with Local Consistency and
  Domain Diversity
Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity
Yuhang Chen
Wenke Huang
Mang Ye
FedML
253
43
0
26 May 2024
Multi-Level Additive Modeling for Structured Non-IID Federated Learning
Multi-Level Additive Modeling for Structured Non-IID Federated Learning
Shutong Chen
Tianyi Zhou
Guodong Long
Jie Ma
Jing Jiang
Chengqi Zhang
FedML
253
2
0
26 May 2024
Vertical Federated Learning for Effectiveness, Security, Applicability:
  A Survey
Vertical Federated Learning for Effectiveness, Security, Applicability: A Survey
Mang Ye
Wei Shen
Bo Du
E. Snezhko
Vassili Kovalev
PongChi Yuen
FedML
327
22
0
25 May 2024
Cooperative Backdoor Attack in Decentralized Reinforcement Learning with
  Theoretical Guarantee
Cooperative Backdoor Attack in Decentralized Reinforcement Learning with Theoretical Guarantee
Mengtong Gao
Yifei Zou
Zuyuan Zhang
Xiuzhen Cheng
Dongxiao Yu
AAML
300
8
0
24 May 2024
A Survey of Distributed Learning in Cloud, Mobile, and Edge Settings
A Survey of Distributed Learning in Cloud, Mobile, and Edge Settings
Madison Threadgill
A. Gerstlauer
164
2
0
23 May 2024
Distributed Continual Learning
Distributed Continual Learning
Long Le
Marcel Hussing
Eric Eaton
CLLFedML
241
2
0
23 May 2024
Variational Bayes for Federated Continual Learning
Variational Bayes for Federated Continual Learning
Dezhong Yao
Sanmu Li
Yutong Dai
Zhiqiang Xu
Shengshan Hu
Peilin Zhao
Lichao Sun
FedML
242
2
0
23 May 2024
Data-Free Federated Class Incremental Learning with Diffusion-Based
  Generative Memory
Data-Free Federated Class Incremental Learning with Diffusion-Based Generative Memory
Naibo Wang
Yuchen Deng
Wenjie Feng
Yuxiang Cai
See-Kiong Ng
DiffMFedML
222
2
0
22 May 2024
Vertical Federated Learning Hybrid Local Pre-training
Vertical Federated Learning Hybrid Local Pre-training
Wenguo Li
Xinling Guo
Xu Jiao
Tiancheng Huang
Xiaoran Yan
Yao Yang
FedML
266
1
0
20 May 2024
FedCAda: Adaptive Client-Side Optimization for Accelerated and Stable
  Federated Learning
FedCAda: Adaptive Client-Side Optimization for Accelerated and Stable Federated Learning
Liuzhi Zhou
Yu He
Kun Zhai
Xiang Liu
Sen Liu
Jiabo He
Guangnan Ye
Yu-Gang Jiang
Hongfeng Chai
FedML
151
5
0
20 May 2024
Distributed Event-Based Learning via ADMM
Distributed Event-Based Learning via ADMM
Güner Dilsad Er
Sebastian Trimpe
Michael Muehlebach
FedML
421
3
0
17 May 2024
Real-World Federated Learning in Radiology: Hurdles to overcome and
  Benefits to gain
Real-World Federated Learning in Radiology: Hurdles to overcome and Benefits to gain
Markus R. Bujotzek
Unal Akunal
Stefan Denner
Peter Neher
M. Zenk
...
Jens Kleesiek
Tobias Penzkofer
Klaus H. Maier-Hein
R. Braren
Andreas Bucher
AI4CE
195
12
0
15 May 2024
SSFL: Discovering Sparse Unified Subnetworks at Initialization for Efficient Federated Learning
SSFL: Discovering Sparse Unified Subnetworks at Initialization for Efficient Federated Learning
Riyasat Ohib
Bishal Thapaliya
Gintare Karolina Dziugaite
Jingyu Liu
Vince D. Calhoun
Sergey Plis
FedML
241
1
0
15 May 2024
Previous
123...678...323334
Next
Page 7 of 34
Pageof 34