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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
Asynchronous Federated Learning with Reduced Number of Rounds and with
  Differential Privacy from Less Aggregated Gaussian Noise
Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise
Marten van Dijk
Nhuong V. Nguyen
Toan N. Nguyen
Lam M. Nguyen
Quoc Tran-Dinh
Phuong Ha Nguyen
FedML
215
30
0
17 Jul 2020
A Survey of Privacy Attacks in Machine Learning
A Survey of Privacy Attacks in Machine LearningACM Computing Surveys (ACM CSUR), 2020
M. Rigaki
Sebastian Garcia
PILMAAML
336
283
0
15 Jul 2020
Joint Device Scheduling and Resource Allocation for Latency Constrained
  Wireless Federated Learning
Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated LearningIEEE Transactions on Wireless Communications (TWC), 2020
Wenqi Shi
Sheng Zhou
Z. Niu
Miao Jiang
Lu Geng
153
336
0
14 Jul 2020
Data-driven geophysics: from dictionary learning to deep learning
Data-driven geophysics: from dictionary learning to deep learning
Siwei Yu
Jianwei Ma
AI4CE
176
9
0
13 Jul 2020
Blockchain-Federated-Learning and Deep Learning Models for COVID-19
  detection using CT Imaging
Blockchain-Federated-Learning and Deep Learning Models for COVID-19 detection using CT ImagingIEEE Sensors Journal (IEEE Sens. J.), 2020
R. Kumar
A. Khan
Sinmin Zhang
Jay Kumar
Wenyong Wang
Yousif Abuidris
Zakria
Waqas Amin
Sidra Shafiq
WenYong Wang
OODFedML
212
369
0
10 Jul 2020
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
Attack of the Tails: Yes, You Really Can Backdoor Federated LearningNeural Information Processing Systems (NeurIPS), 2020
Hongyi Wang
Kartik K. Sreenivasan
Shashank Rajput
Harit Vishwakarma
Saurabh Agarwal
Jy-yong Sohn
Kangwook Lee
Dimitris Papailiopoulos
FedML
271
735
0
09 Jul 2020
Learning while Respecting Privacy and Robustness to Distributional
  Uncertainties and Adversarial Data
Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data
A. Sadeghi
Gang Wang
Meng Ma
G. Giannakis
OODFedML
111
4
0
07 Jul 2020
Tilted Empirical Risk Minimization
Tilted Empirical Risk Minimization
Tian Li
Ahmad Beirami
Maziar Sanjabi
Virginia Smith
380
144
0
02 Jul 2020
Federated Learning with Compression: Unified Analysis and Sharp
  Guarantees
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour
Mohammad Mahdi Kamani
Aryan Mokhtari
M. Mahdavi
FedML
443
313
0
02 Jul 2020
On the Outsized Importance of Learning Rates in Local Update Methods
On the Outsized Importance of Learning Rates in Local Update Methods
Zachary B. Charles
Jakub Konecný
FedML
215
57
0
02 Jul 2020
Local Stochastic Approximation: A Unified View of Federated Learning and
  Distributed Multi-Task Reinforcement Learning Algorithms
Local Stochastic Approximation: A Unified View of Federated Learning and Distributed Multi-Task Reinforcement Learning Algorithms
Thinh T. Doan
FedML
200
10
0
24 Jun 2020
Exact Support Recovery in Federated Regression with One-shot
  Communication
Exact Support Recovery in Federated Regression with One-shot Communication
Adarsh Barik
Jean Honorio
FedML
106
2
0
22 Jun 2020
Technology Readiness Levels for AI & ML
Technology Readiness Levels for AI & ML
Alexander Lavin
Ajay Sharma
VLM
244
141
0
21 Jun 2020
Optimal and Practical Algorithms for Smooth and Strongly Convex
  Decentralized Optimization
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization
D. Kovalev
Adil Salim
Peter Richtárik
276
96
0
21 Jun 2020
Federated Learning Meets Multi-objective Optimization
Federated Learning Meets Multi-objective Optimization
Zeou Hu
Kiarash Shaloudegi
Guojun Zhang
Yaoliang Yu
FedML
225
124
0
20 Jun 2020
DEED: A General Quantization Scheme for Communication Efficiency in Bits
DEED: A General Quantization Scheme for Communication Efficiency in Bits
Tian-Chun Ye
Peijun Xiao
Tian Ding
FedMLMQ
86
2
0
19 Jun 2020
Federated Learning With Quantized Global Model Updates
Federated Learning With Quantized Global Model Updates
M. Amiri
Deniz Gunduz
Sanjeev R. Kulkarni
H. Vincent Poor
FedML
248
145
0
18 Jun 2020
Differentially-private Federated Neural Architecture Search
Differentially-private Federated Neural Architecture Search
Ishika Singh
Haoyi Zhou
Kunlin Yang
Mengxiao Ding
Bill Lin
P. Xie
FedML
174
24
0
16 Jun 2020
Robust Federated Learning: The Case of Affine Distribution Shifts
Robust Federated Learning: The Case of Affine Distribution Shifts
Amirhossein Reisizadeh
Farzan Farnia
Ramtin Pedarsani
Ali Jadbabaie
FedMLOOD
265
181
0
16 Jun 2020
Personalized Federated Learning with Moreau Envelopes
Personalized Federated Learning with Moreau Envelopes
Canh T. Dinh
N. H. Tran
Tuan Dung Nguyen
FedML
382
1,238
0
16 Jun 2020
Ensemble Distillation for Robust Model Fusion in Federated Learning
Ensemble Distillation for Robust Model Fusion in Federated LearningNeural Information Processing Systems (NeurIPS), 2020
Tao Lin
Lingjing Kong
Sebastian U. Stich
Martin Jaggi
FedML
578
1,304
0
12 Jun 2020
Characterizing Impacts of Heterogeneity in Federated Learning upon
  Large-Scale Smartphone Data
Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data
Chengxu Yang
Qipeng Wang
Mengwei Xu
Shangguang Wang
Kaigui Bian
Yunxin Liu
Xuanzhe Liu
171
24
0
12 Jun 2020
XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated
  Learning
XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning
Myungjae Shin
Chihoon Hwang
Joongheon Kim
Jihong Park
M. Bennis
Seong-Lyun Kim
FedML
203
120
0
09 Jun 2020
UVeQFed: Universal Vector Quantization for Federated Learning
UVeQFed: Universal Vector Quantization for Federated Learning
Stefano Rini
Mingzhe Chen
Yonina C. Eldar
H. Vincent Poor
Shuguang Cui
FedMLMQ
256
260
0
05 Jun 2020
Federated Learning for 6G Communications: Challenges, Methods, and
  Future Directions
Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
Yi Liu
Lizhen Qu
Zehui Xiong
Jiawen Kang
Xiaofei Wang
Dusit Niyato
FedMLAI4CE
189
311
0
04 Jun 2020
Secure Sum Outperforms Homomorphic Encryption in (Current) Collaborative
  Deep Learning
Secure Sum Outperforms Homomorphic Encryption in (Current) Collaborative Deep Learning
Derian Boer
Stefan Kramer
FedML
122
10
0
02 Jun 2020
Federated Learning in Vehicular Networks
Federated Learning in Vehicular NetworksInternational Mediterranean Conference on Communications and Networking (MCN), 2020
Ahmet M. Elbir
Burak Soner
Sinem Coleri
Deniz Gunduz
M. Bennis
228
204
0
02 Jun 2020
Federated Face Presentation Attack Detection
Federated Face Presentation Attack Detection
Rui Shao
Pramuditha Perera
Pong C. Yuen
Vishal M. Patel
CVBMFedML
136
6
0
29 May 2020
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity
  to Non-IID Data
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data
Xinwei Zhang
Mingyi Hong
S. Dhople
W. Yin
Yang Liu
FedML
321
262
0
22 May 2020
Distilling Knowledge from Ensembles of Acoustic Models for Joint
  CTC-Attention End-to-End Speech Recognition
Distilling Knowledge from Ensembles of Acoustic Models for Joint CTC-Attention End-to-End Speech Recognition
Yan Gao
Titouan Parcollet
Nicholas D. Lane
VLM
178
15
0
19 May 2020
Scaling-up Distributed Processing of Data Streams for Machine Learning
Scaling-up Distributed Processing of Data Streams for Machine Learning
M. Nokleby
Haroon Raja
W. Bajwa
207
18
0
18 May 2020
New Frontiers in IoT: Networking, Systems, Reliability, and Security
  Challenges
New Frontiers in IoT: Networking, Systems, Reliability, and Security Challenges
S. Bagchi
Tarek Abdelzaher
R. Govindan
Prashant J. Shenoy
Akanksha Atrey
Pradipta Ghosh
Ran Xu
184
53
0
15 May 2020
A Secure Federated Learning Framework for 5G Networks
A Secure Federated Learning Framework for 5G Networks
Yi Liu
Jia-Jie Peng
Jiawen Kang
Abdullah M. Iliyasu
Dusit Niyato
A. El-latif
FedML
111
224
0
12 May 2020
FedSplit: An algorithmic framework for fast federated optimization
FedSplit: An algorithmic framework for fast federated optimization
Reese Pathak
Martin J. Wainwright
FedML
361
204
0
11 May 2020
Federated Generative Adversarial Learning
Federated Generative Adversarial Learning
Chenyou Fan
Ping Liu
GANFedML
386
50
0
07 May 2020
Information-Theoretic Bounds on the Generalization Error and Privacy
  Leakage in Federated Learning
Information-Theoretic Bounds on the Generalization Error and Privacy Leakage in Federated LearningInternational Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2020
Semih Yagli
Alex Dytso
H. Vincent Poor
FedML
147
35
0
05 May 2020
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated LearningACM Transactions on Knowledge Discovery from Data (TKDD), 2020
Xinjian Luo
Xiangqi Zhu
FedML
659
30
0
27 Apr 2020
Towards Ubiquitous AI in 6G with Federated Learning
Towards Ubiquitous AI in 6G with Federated Learning
Yong Xiao
Guangming Shi
Marwan Krunz
FedML
121
46
0
26 Apr 2020
Federated learning with hierarchical clustering of local updates to
  improve training on non-IID data
Federated learning with hierarchical clustering of local updates to improve training on non-IID dataIEEE International Joint Conference on Neural Network (IJCNN), 2020
Christopher Briggs
Zhong Fan
Péter András
FedML
213
696
0
24 Apr 2020
Federated Learning with Only Positive Labels
Federated Learning with Only Positive Labels
Felix X. Yu
A. S. Rawat
A. Menon
Sanjiv Kumar
FedML
180
121
0
21 Apr 2020
Have you forgotten? A method to assess if machine learning models have
  forgotten data
Have you forgotten? A method to assess if machine learning models have forgotten data
Xiao Liu
Sotirios A. Tsaftaris
FedMLOODMU
109
27
0
21 Apr 2020
Secret Sharing based Secure Regressions with Applications
Secret Sharing based Secure Regressions with Applications
Chaochao Chen
Liang Li
Wenjing Fang
Jun Zhou
Li Wang
Lei Wang
Shuang Yang
A. Liu
Hongya Wang
125
4
0
10 Apr 2020
Dualize, Split, Randomize: Toward Fast Nonsmooth Optimization Algorithms
Dualize, Split, Randomize: Toward Fast Nonsmooth Optimization AlgorithmsJournal of Optimization Theory and Applications (JOTA), 2020
Adil Salim
Laurent Condat
Konstantin Mishchenko
Peter Richtárik
277
28
0
03 Apr 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive
  Strategies
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies
David Enthoven
Zaid Al-Ars
FedML
167
59
0
01 Apr 2020
Federated Residual Learning
Federated Residual Learning
Alekh Agarwal
John Langford
Chen-Yu Wei
FedML
157
41
0
28 Mar 2020
Edge Intelligence: Architectures, Challenges, and Applications
Edge Intelligence: Architectures, Challenges, and Applications
Dianlei Xu
Tong Li
Yong Li
Xiang Su
Sasu Tarkoma
Tao Jiang
Jon Crowcroft
Pan Hui
264
30
0
26 Mar 2020
Privacy-preserving Traffic Flow Prediction: A Federated Learning
  Approach
Privacy-preserving Traffic Flow Prediction: A Federated Learning ApproachIEEE Internet of Things Journal (IEEE IoT J.), 2020
Yi Liu
James Jianqiao Yu
Jiawen Kang
Dusit Niyato
Shuyu Zhang
AI4TS
165
516
0
19 Mar 2020
The Future of Digital Health with Federated Learning
The Future of Digital Health with Federated Learningnpj Digital Medicine (NPJ Digit Med), 2020
Nicola Rieke
Jonny Hancox
Wenqi Li
Fausto Milletari
H. Roth
...
Ronald M. Summers
Andrew Trask
Daguang Xu
Maximilian Baust
M. Jorge Cardoso
OOD
484
2,269
0
18 Mar 2020
Federated Visual Classification with Real-World Data Distribution
Federated Visual Classification with Real-World Data DistributionEuropean Conference on Computer Vision (ECCV), 2020
T. Hsu
Qi
Matthew Brown
FedML
326
234
0
18 Mar 2020
Ternary Compression for Communication-Efficient Federated Learning
Ternary Compression for Communication-Efficient Federated LearningIEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020
Jinjin Xu
W. Du
Ran Cheng
Wangli He
Yaochu Jin
MQFedML
181
195
0
07 Mar 2020
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