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. 1912.04977
  4. Cited By
Advances and Open Problems in Federated Learning
v1v2v3 (latest)

Advances and Open Problems in Federated Learning

10 December 2019
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
A. Bhagoji
Keith Bonawitz
Zachary B. Charles
Graham Cormode
Rachel Cummings
Rafael G. L. DÓliveira
Hubert Eichner
S. E. Rouayheb
David Evans
Josh Gardner
Zachary Garrett
Adria Gascon
Badih Ghazi
Phillip B. Gibbons
Marco Gruteser
Zaïd Harchaoui
Chaoyang He
Lie He
Zhouyuan Huo
Ben Hutchinson
Justin Hsu
Martin Jaggi
T. Javidi
Gauri Joshi
M. Khodak
Jakub Konecný
Aleksandra Korolova
F. Koushanfar
Oluwasanmi Koyejo
Tancrède Lepoint
Yang Liu
Prateek Mittal
M. Mohri
Richard Nock
A. Özgür
Rasmus Pagh
Mariana Raykova
Hang Qi
Daniel Ramage
Ramesh Raskar
Basel Alomair
Weikang Song
Sebastian U. Stich
Ziteng Sun
A. Suresh
Florian Tramèr
Praneeth Vepakomma
Jianyu Wang
Li Xiong
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
    FedMLAI4CE
ArXiv (abs)PDFHTML

Papers citing "Advances and Open Problems in Federated Learning"

50 / 2,962 papers shown
Differentially Private Distributed Computation via Public-Private
  Communication Networks
Differentially Private Distributed Computation via Public-Private Communication Networks
Lei Wang
Yang Liu
I. Manchester
Guodong Shi
FedML
113
3
0
05 Jan 2021
First-Order Methods for Convex Optimization
First-Order Methods for Convex OptimizationEURO Journal on Computational Optimization (EJCO), 2021
Pavel Dvurechensky
Mathias Staudigl
Shimrit Shtern
ODL
283
28
0
04 Jan 2021
Device Sampling for Heterogeneous Federated Learning: Theory,
  Algorithms, and Implementation
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and ImplementationIEEE Conference on Computer Communications (INFOCOM), 2021
Su Wang
Mengyuan Lee
Seyyedali Hosseinalipour
Roberto Morabito
M. Chiang
Christopher G. Brinton
FedML
264
128
0
04 Jan 2021
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
Binbin Guo
Yuan Mei
Danyang Xiao
Weigang Wu
Ye Yin
Hongli Chang
MoE
258
30
0
31 Dec 2020
CADA: Communication-Adaptive Distributed Adam
CADA: Communication-Adaptive Distributed AdamInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Tianyi Chen
Ziye Guo
Yuejiao Sun
W. Yin
ODL
169
24
0
31 Dec 2020
Straggler-Resilient Federated Learning: Leveraging the Interplay Between
  Statistical Accuracy and System Heterogeneity
Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System HeterogeneityIEEE Journal on Selected Areas in Information Theory (JSAIT), 2020
Amirhossein Reisizadeh
Isidoros Tziotis
Hamed Hassani
Aryan Mokhtari
Ramtin Pedarsani
FedML
391
131
0
28 Dec 2020
Federated Unlearning
Federated Unlearning
Gaoyang Liu
Xiaoqiang Ma
Yang Yang
Chen Wang
Jiangchuan Liu
MU
327
72
0
27 Dec 2020
Decentralized Federated Learning via Mutual Knowledge Transfer
Decentralized Federated Learning via Mutual Knowledge TransferIEEE Internet of Things Journal (IEEE IoT J.), 2020
Chengxi Li
Gang Li
P. Varshney
FedML
327
133
0
24 Dec 2020
EQ-Net: A Unified Deep Learning Framework for Log-Likelihood Ratio
  Estimation and Quantization
EQ-Net: A Unified Deep Learning Framework for Log-Likelihood Ratio Estimation and Quantization
Marius Arvinte
Ahmed H. Tewfik
S. Vishwanath
MQ
152
0
0
23 Dec 2020
AutonoML: Towards an Integrated Framework for Autonomous Machine
  Learning
AutonoML: Towards an Integrated Framework for Autonomous Machine Learning
D. Kedziora
Katarzyna Musial
Bogdan Gabrys
289
18
0
23 Dec 2020
Comparison of Privacy-Preserving Distributed Deep Learning Methods in
  Healthcare
Comparison of Privacy-Preserving Distributed Deep Learning Methods in HealthcareAnnual Conference on Medical Image Understanding and Analysis (MIUA), 2020
M. Gawali
S. ArvindC.
Shriya Suryavanshi
Harshit Madaan
A. Gaikwad
KN BhanuPrakash
V. Kulkarni
Aniruddha Pant
FedML
198
38
0
23 Dec 2020
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep
  neural networks
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networksComputer Vision and Pattern Recognition (CVPR), 2020
Abhishek Singh
Ayush Chopra
Vivek Sharma
Ethan Garza
Emily Zhang
Praneeth Vepakomma
Ramesh Raskar
255
58
0
20 Dec 2020
Toward Understanding the Influence of Individual Clients in Federated
  Learning
Toward Understanding the Influence of Individual Clients in Federated LearningAAAI Conference on Artificial Intelligence (AAAI), 2020
Yihao Xue
Chaoyue Niu
Zhenzhe Zheng
Shaojie Tang
Chengfei Lv
Fan Wu
Guihai Chen
FedML
377
44
0
20 Dec 2020
Learning from History for Byzantine Robust Optimization
Learning from History for Byzantine Robust OptimizationInternational Conference on Machine Learning (ICML), 2020
Sai Praneeth Karimireddy
Lie He
Martin Jaggi
FedMLAAML
392
226
0
18 Dec 2020
FedeRank: User Controlled Feedback with Federated Recommender Systems
FedeRank: User Controlled Feedback with Federated Recommender SystemsEuropean Conference on Information Retrieval (ECIR), 2020
Vito Walter Anelli
Yashar Deldjoo
Tommaso Di Noia
Antonio Ferrara
Fedelucio Narducci
FedML
257
46
0
15 Dec 2020
Personalized Federated Learning with First Order Model Optimization
Personalized Federated Learning with First Order Model OptimizationInternational Conference on Learning Representations (ICLR), 2020
Michael Zhang
Karan Sapra
Sanja Fidler
Serena Yeung
J. Álvarez
FedML
343
377
0
15 Dec 2020
Cost-Effective Federated Learning Design
Cost-Effective Federated Learning DesignIEEE Conference on Computer Communications (INFOCOM), 2020
Bing Luo
Xiang Li
Maroun Touma
Jianwei Huang
Leandros Tassiulas
FedML
273
209
0
15 Dec 2020
CosSGD: Communication-Efficient Federated Learning with a Simple
  Cosine-Based Quantization
CosSGD: Communication-Efficient Federated Learning with a Simple Cosine-Based Quantization
Yang He
Hui-Po Wang
M. Zenk
Mario Fritz
FedMLMQ
227
10
0
15 Dec 2020
Towards open and expandable cognitive AI architectures for large-scale
  multi-agent human-robot collaborative learning
Towards open and expandable cognitive AI architectures for large-scale multi-agent human-robot collaborative learningIEEE Access (IEEE Access), 2020
Georgios Th. Papadopoulos
M. Antona
C. Stephanidis
AI4CE
237
35
0
15 Dec 2020
Bandit-based Communication-Efficient Client Selection Strategies for
  Federated Learning
Bandit-based Communication-Efficient Client Selection Strategies for Federated LearningAsilomar Conference on Signals, Systems and Computers (Asilomar), 2020
Yae Jee Cho
Samarth Gupta
Gauri Joshi
Osman Yağan
FedML
255
80
0
14 Dec 2020
FedHome: Cloud-Edge based Personalized Federated Learning for In-Home
  Health Monitoring
FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health MonitoringIEEE Transactions on Mobile Computing (IEEE TMC), 2020
Qiong Wu
Xu Chen
Zhi Zhou
Junshan Zhang
FedML
341
360
0
14 Dec 2020
Achieving Security and Privacy in Federated Learning Systems: Survey,
  Research Challenges and Future Directions
Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future DirectionsEngineering applications of artificial intelligence (EAAI), 2020
Alberto Blanco-Justicia
J. Domingo-Ferrer
Sergio Martínez
David Sánchez
Adrian Flanagan
K. E. Tan
FedML
143
134
0
12 Dec 2020
Communication-Efficient Federated Learning with Compensated
  Overlap-FedAvg
Communication-Efficient Federated Learning with Compensated Overlap-FedAvgIEEE Transactions on Parallel and Distributed Systems (TPDS), 2020
Yuhao Zhou
Qing Ye
Jiancheng Lv
FedML
243
171
0
12 Dec 2020
Analysis and Optimal Edge Assignment For Hierarchical Federated Learning
  on Non-IID Data
Analysis and Optimal Edge Assignment For Hierarchical Federated Learning on Non-IID Data
N. Mhaisen
Alaa Awad
Amr M. Mohamed
A. Erbad
Mohsen Guizani
FedML
237
14
0
10 Dec 2020
Communication-Computation Efficient Secure Aggregation for Federated
  Learning
Communication-Computation Efficient Secure Aggregation for Federated Learning
Beongjun Choi
Jy-yong Sohn
Dong-Jun Han
Jaekyun Moon
FedML
323
111
0
10 Dec 2020
Research Challenges in Designing Differentially Private Text Generation
  Mechanisms
Research Challenges in Designing Differentially Private Text Generation MechanismsThe Florida AI Research Society (FLAIRS), 2020
Oluwaseyi Feyisetan
Abhinav Aggarwal
Zekun Xu
Nathanael Teissier
240
11
0
10 Dec 2020
Privacy Amplification by Decentralization
Privacy Amplification by DecentralizationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Edwige Cyffers
A. Bellet
FedML
459
45
0
09 Dec 2020
Federated Learning in Unreliable and Resource-Constrained Cellular
  Wireless Networks
Federated Learning in Unreliable and Resource-Constrained Cellular Wireless NetworksIEEE Transactions on Communications (IEEE Trans. Commun.), 2020
M. Salehi
Ekram Hossain
FedML
223
101
0
09 Dec 2020
GraphFL: A Federated Learning Framework for Semi-Supervised Node
  Classification on Graphs
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs
Binghui Wang
Ang Li
Xue Yang
Yiran Chen
200
138
0
08 Dec 2020
Design and Analysis of Uplink and Downlink Communications for Federated
  Learning
Design and Analysis of Uplink and Downlink Communications for Federated Learning
Sihui Zheng
Cong Shen
Xiang Chen
233
177
0
07 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses
Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu
Han Yu
Jiabo He
Chen Chen
Lichao Sun
Jun Zhao
Qiang Yang
Philip S. Yu
FedML
605
479
0
07 Dec 2020
Vehicular Cooperative Perception Through Action Branching and Federated
  Reinforcement Learning
Vehicular Cooperative Perception Through Action Branching and Federated Reinforcement LearningIEEE Transactions on Communications (IEEE Trans. Commun.), 2020
Mohamed K. Abdel-Aziz
Cristina Perfecto
S. Samarakoon
M. Bennis
Walid Saad
371
66
0
07 Dec 2020
SoK: Training Machine Learning Models over Multiple Sources with Privacy
  Preservation
SoK: Training Machine Learning Models over Multiple Sources with Privacy Preservation
Lushan Song
Guopeng Lin
Jiaxuan Wang
Haoqi Wu
Wenqiang Ruan
Weili Han
402
9
0
06 Dec 2020
Probabilistic Federated Learning of Neural Networks Incorporated with Global Posterior Information
Peng Xiao
Samuel Cheng
FedML
244
1
0
06 Dec 2020
Federated Learning with Heterogeneous Labels and Models for Mobile
  Activity Monitoring
Federated Learning with Heterogeneous Labels and Models for Mobile Activity Monitoring
Gautham Krishna Gudur
S. K. Perepu
FedML
122
54
0
04 Dec 2020
Mitigating Bias in Federated Learning
Mitigating Bias in Federated Learning
Annie Abay
Yi Zhou
Nathalie Baracaldo
Shashank Rajamoni
Ebube Chuba
Heiko Ludwig
AI4CE
194
110
0
04 Dec 2020
FAT: Federated Adversarial Training
FAT: Federated Adversarial Training
Giulio Zizzo
Ambrish Rawat
M. Sinn
Beat Buesser
FedML
174
52
0
03 Dec 2020
Federated Learning for Personalized Humor Recognition
Federated Learning for Personalized Humor RecognitionACM Transactions on Intelligent Systems and Technology (ACM TIST), 2020
Xu Guo
Han Yu
Boyang Albert Li
Hao Wang
Pengwei Xing
Siwei Feng
Zaiqing Nie
Chunyan Miao
FedML
239
14
0
03 Dec 2020
Global and Individualized Community Detection in Inhomogeneous
  Multilayer Networks
Global and Individualized Community Detection in Inhomogeneous Multilayer NetworksAnnals of Statistics (Ann. Stat.), 2020
Shuxiao Chen
Sifan Liu
Zongming Ma
315
35
0
02 Dec 2020
Communication-Efficient Federated Distillation
Communication-Efficient Federated Distillation
Felix Sattler
Arturo Marbán
R. Rischke
Wojciech Samek
FedMLDD
247
41
0
01 Dec 2020
Edge-assisted Democratized Learning Towards Federated Analytics
Edge-assisted Democratized Learning Towards Federated AnalyticsIEEE Internet of Things Journal (IEEE IoT J.), 2020
Shashi Raj Pandey
Minh N. H. Nguyen
Tri Nguyen Dang
N. H. Tran
K. Thar
Zhu Han
Choong Seon Hong
FedML
313
26
0
01 Dec 2020
A Systematic Literature Review on Federated Learning: From A Model
  Quality Perspective
A Systematic Literature Review on Federated Learning: From A Model Quality Perspective
Yi Liu
Li Zhang
Ning Ge
Guanghao Li
FedML
227
31
0
01 Dec 2020
Advancements of federated learning towards privacy preservation: from
  federated learning to split learning
Advancements of federated learning towards privacy preservation: from federated learning to split learning
Chandra Thapa
Pathum Chamikara Mahawaga Arachchige
S. Çamtepe
FedML
168
99
0
25 Nov 2020
MetaGater: Fast Learning of Conditional Channel Gated Networks via
  Federated Meta-Learning
MetaGater: Fast Learning of Conditional Channel Gated Networks via Federated Meta-LearningIEEE International Conference on Mobile Adhoc and Sensor Systems (MASS), 2020
Sen Lin
Li Yang
Zhezhi He
Deliang Fan
Junshan Zhang
FedMLAI4CE
217
6
0
25 Nov 2020
Toward Multiple Federated Learning Services Resource Sharing in Mobile
  Edge Networks
Toward Multiple Federated Learning Services Resource Sharing in Mobile Edge NetworksIEEE Transactions on Mobile Computing (IEEE TMC), 2020
Minh N. H. Nguyen
N. H. Tran
Y. Tun
Zhu Han
Choong Seon Hong
FedML
194
55
0
25 Nov 2020
Wyner-Ziv Estimators for Distributed Mean Estimation with Side
  Information and Optimization
Wyner-Ziv Estimators for Distributed Mean Estimation with Side Information and OptimizationIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Prathamesh Mayekar
Shubham K. Jha
A. Suresh
Himanshu Tyagi
FedML
275
2
0
24 Nov 2020
When Machine Learning Meets Privacy: A Survey and Outlook
When Machine Learning Meets Privacy: A Survey and OutlookACM Computing Surveys (ACM CSUR), 2020
B. Liu
Ming Ding
Sina shaham
W. Rahayu
F. Farokhi
Zihuai Lin
282
328
0
24 Nov 2020
LINDT: Tackling Negative Federated Learning with Local Adaptation
LINDT: Tackling Negative Federated Learning with Local Adaptation
Hong Lin
Lidan Shou
Ke Chen
Gang Chen
Sai Wu
FedML
128
0
0
23 Nov 2020
On the Benefits of Multiple Gossip Steps in Communication-Constrained
  Decentralized Optimization
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization
Abolfazl Hashemi
Anish Acharya
Rudrajit Das
H. Vikalo
Sujay Sanghavi
Inderjit Dhillon
281
9
0
20 Nov 2020
A Reputation Mechanism Is All You Need: Collaborative Fairness and
  Adversarial Robustness in Federated Learning
A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in Federated Learning
Xinyi Xu
Lingjuan Lyu
FedML
219
88
0
20 Nov 2020
Previous
123...535455...585960
Next
Page 54 of 60
Pageof 60