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Federated Learning: Challenges, Methods, and Future Directions

Federated Learning: Challenges, Methods, and Future Directions

21 August 2019
Tian Li
Anit Kumar Sahu
Ameet Talwalkar
Virginia Smith
    FedML
ArXivPDFHTML

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

50 / 549 papers shown
Title
Low-Latency Federated Learning over Wireless Channels with Differential
  Privacy
Low-Latency Federated Learning over Wireless Channels with Differential Privacy
Kang Wei
Jun Li
Chuan Ma
Ming Ding
Cailian Chen
Shi Jin
Zhu Han
H. Vincent Poor
FedML
27
73
0
20 Jun 2021
Zero-Shot Federated Learning with New Classes for Audio Classification
Zero-Shot Federated Learning with New Classes for Audio Classification
Gautham Krishna Gudur
S. K. Perepu
FedML
13
10
0
18 Jun 2021
Optimality and Stability in Federated Learning: A Game-theoretic
  Approach
Optimality and Stability in Federated Learning: A Game-theoretic Approach
Kate Donahue
Jon M. Kleinberg
FedML
13
45
0
17 Jun 2021
Privacy Assessment of Federated Learning using Private Personalized
  Layers
Privacy Assessment of Federated Learning using Private Personalized Layers
T. Jourdan
A. Boutet
Carole Frindel
FedML
42
7
0
15 Jun 2021
On Large-Cohort Training for Federated Learning
On Large-Cohort Training for Federated Learning
Zachary B. Charles
Zachary Garrett
Zhouyuan Huo
Sergei Shmulyian
Virginia Smith
FedML
21
113
0
15 Jun 2021
Dynamic Gradient Aggregation for Federated Domain Adaptation
Dynamic Gradient Aggregation for Federated Domain Adaptation
Dimitrios Dimitriadis
K. Kumatani
R. Gmyr
Yashesh Gaur
Sefik Emre Eskimez
FedML
20
5
0
14 Jun 2021
Federated Learning with Spiking Neural Networks
Federated Learning with Spiking Neural Networks
Yeshwanth Venkatesha
Youngeun Kim
Leandros Tassiulas
Priyadarshini Panda
FedML
25
47
0
11 Jun 2021
What Can Knowledge Bring to Machine Learning? -- A Survey of Low-shot
  Learning for Structured Data
What Can Knowledge Bring to Machine Learning? -- A Survey of Low-shot Learning for Structured Data
Yang Hu
Adriane P. Chapman
Guihua Wen
Dame Wendy Hall
42
24
0
11 Jun 2021
Rethinking Architecture Design for Tackling Data Heterogeneity in
  Federated Learning
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning
Liangqiong Qu
Yuyin Zhou
Paul Pu Liang
Yingda Xia
Feifei Wang
Ehsan Adeli
L. Fei-Fei
D. Rubin
FedML
AI4CE
19
174
0
10 Jun 2021
No Fear of Heterogeneity: Classifier Calibration for Federated Learning
  with Non-IID Data
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
Mi Luo
Fei Chen
Dapeng Hu
Yifan Zhang
Jian Liang
Jiashi Feng
FedML
28
327
0
09 Jun 2021
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections
  to Weight-Sharing
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
M. Khodak
Renbo Tu
Tian Li
Liam Li
Maria-Florina Balcan
Virginia Smith
Ameet Talwalkar
FedML
35
78
0
08 Jun 2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning
FedNL: Making Newton-Type Methods Applicable to Federated Learning
M. Safaryan
Rustem Islamov
Xun Qian
Peter Richtárik
FedML
20
77
0
05 Jun 2021
H-FL: A Hierarchical Communication-Efficient and Privacy-Protected
  Architecture for Federated Learning
H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning
He Yang
14
27
0
01 Jun 2021
Recent advances and clinical applications of deep learning in medical
  image analysis
Recent advances and clinical applications of deep learning in medical image analysis
Xuxin Chen
Ximing Wang
Kecheng Zhang
K. Fung
T. Thai
K. Moore
Robert S. Mannel
Hong Liu
B. Zheng
Y. Qiu
OOD
18
570
0
27 May 2021
Concept drift detection and adaptation for federated and continual
  learning
Concept drift detection and adaptation for federated and continual learning
F. Casado
Dylan Lema
Marcos F. Criado
R. Iglesias
Carlos V. Regueiro
S. Barro
FedML
8
63
0
27 May 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning
Data-Free Knowledge Distillation for Heterogeneous Federated Learning
Zhuangdi Zhu
Junyuan Hong
Jiayu Zhou
FedML
22
627
0
20 May 2021
Federated Learning With Highly Imbalanced Audio Data
Federated Learning With Highly Imbalanced Audio Data
Marc C. Green
Mark D. Plumbley
FedML
14
3
0
18 May 2021
A Fusion-Denoising Attack on InstaHide with Data Augmentation
A Fusion-Denoising Attack on InstaHide with Data Augmentation
Xinjian Luo
X. Xiao
Yuncheng Wu
Juncheng Liu
Beng Chin Ooi
FedML
PICV
52
7
0
17 May 2021
EasyFL: A Low-code Federated Learning Platform For Dummies
EasyFL: A Low-code Federated Learning Platform For Dummies
Weiming Zhuang
Xin Gan
Yonggang Wen
Shuai Zhang
FedML
19
46
0
17 May 2021
Coded Gradient Aggregation: A Tradeoff Between Communication Costs at
  Edge Nodes and at Helper Nodes
Coded Gradient Aggregation: A Tradeoff Between Communication Costs at Edge Nodes and at Helper Nodes
B. Sasidharan
Anoop Thomas
23
9
0
06 May 2021
Pervasive AI for IoT applications: A Survey on Resource-efficient
  Distributed Artificial Intelligence
Pervasive AI for IoT applications: A Survey on Resource-efficient Distributed Artificial Intelligence
Emna Baccour
N. Mhaisen
A. Abdellatif
A. Erbad
Amr M. Mohamed
Mounir Hamdi
Mohsen Guizani
26
86
0
04 May 2021
Quality Assurance Challenges for Machine Learning Software Applications
  During Software Development Life Cycle Phases
Quality Assurance Challenges for Machine Learning Software Applications During Software Development Life Cycle Phases
Md. Abdullah Al Alamin
Gias Uddin
29
11
0
03 May 2021
From Distributed Machine Learning to Federated Learning: A Survey
From Distributed Machine Learning to Federated Learning: A Survey
Ji Liu
Jizhou Huang
Yang Zhou
Xuhong Li
Shilei Ji
Haoyi Xiong
Dejing Dou
FedML
OOD
51
243
0
29 Apr 2021
End-to-End Speech Recognition from Federated Acoustic Models
End-to-End Speech Recognition from Federated Acoustic Models
Yan Gao
Titouan Parcollet
Salah Zaiem
Javier Fernandez-Marques
Pedro Porto Buarque de Gusmão
Daniel J. Beutel
Nicholas D. Lane
17
43
0
29 Apr 2021
Semi-Decentralized Federated Edge Learning for Fast Convergence on
  Non-IID Data
Semi-Decentralized Federated Edge Learning for Fast Convergence on Non-IID Data
Yuchang Sun
Jiawei Shao
Yuyi Mao
Jessie Hui Wang
Jun Zhang
FedML
26
39
0
26 Apr 2021
FedDPGAN: Federated Differentially Private Generative Adversarial
  Networks Framework for the Detection of COVID-19 Pneumonia
FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumonia
Longling Zhang
Bochen Shen
A. Barnawi
Shan Xi
Neeraj Kumar
Yi Wu
FedML
MedIm
71
80
0
26 Apr 2021
Decentralized Federated Averaging
Decentralized Federated Averaging
Tao Sun
Dongsheng Li
Bao Wang
FedML
40
207
0
23 Apr 2021
A Survey on Federated Learning and its Applications for Accelerating
  Industrial Internet of Things
A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things
Jiehan Zhou
Shouhua Zhang
Qinghua Lu
W. Dai
Min Chen
Xin Liu
Susanna Pirttikangas
Yang Shi
Weishan Zhang
E. Herrera-Viedma
FedML
AI4CE
17
44
0
21 Apr 2021
Sample-based and Feature-based Federated Learning for Unconstrained and
  Constrained Nonconvex Optimization via Mini-batch SSCA
Sample-based and Feature-based Federated Learning for Unconstrained and Constrained Nonconvex Optimization via Mini-batch SSCA
Ying Cui
Yangchen Li
Chencheng Ye
FedML
11
7
0
13 Apr 2021
Distributed Learning in Wireless Networks: Recent Progress and Future
  Challenges
Distributed Learning in Wireless Networks: Recent Progress and Future Challenges
Mingzhe Chen
Deniz Gündüz
Kaibin Huang
Walid Saad
M. Bennis
Aneta Vulgarakis Feljan
H. Vincent Poor
35
401
0
05 Apr 2021
Federated Few-Shot Learning with Adversarial Learning
Federated Few-Shot Learning with Adversarial Learning
Chenyou Fan
Jianwei Huang
FedML
13
29
0
01 Apr 2021
Federated Learning: A Signal Processing Perspective
Federated Learning: A Signal Processing Perspective
Tomer Gafni
Nir Shlezinger
Kobi Cohen
Yonina C. Eldar
H. Vincent Poor
FedML
21
128
0
31 Mar 2021
Threshold-Based Data Exclusion Approach for Energy-Efficient Federated
  Edge Learning
Threshold-Based Data Exclusion Approach for Energy-Efficient Federated Edge Learning
A. Albaseer
M. Abdallah
Ala I. Al-Fuqaha
A. Erbad
27
12
0
30 Mar 2021
FedCor: Correlation-Based Active Client Selection Strategy for
  Heterogeneous Federated Learning
FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning
Minxue Tang
Xuefei Ning
Yitu Wang
Jingwei Sun
Yu Wang
H. Li
Yiran Chen
FedML
21
80
0
24 Mar 2021
Federated Quantum Machine Learning
Federated Quantum Machine Learning
Samuel Yen-Chi Chen
Shinjae Yoo
FedML
AI4CE
16
115
0
22 Mar 2021
Semi-Decentralized Federated Learning with Cooperative D2D Local Model
  Aggregations
Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations
F. Lin
Seyyedali Hosseinalipour
Sheikh Shams Azam
Christopher G. Brinton
Nicolò Michelusi
FedML
19
109
0
18 Mar 2021
Membership Inference Attacks on Machine Learning: A Survey
Membership Inference Attacks on Machine Learning: A Survey
Hongsheng Hu
Z. Salcic
Lichao Sun
Gillian Dobbie
Philip S. Yu
Xuyun Zhang
MIACV
30
412
0
14 Mar 2021
A Study of Face Obfuscation in ImageNet
A Study of Face Obfuscation in ImageNet
Kaiyu Yang
Jacqueline Yau
Li Fei-Fei
Jia Deng
Olga Russakovsky
PICV
CVBM
30
144
0
10 Mar 2021
Convergence and Accuracy Trade-Offs in Federated Learning and
  Meta-Learning
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning
Zachary B. Charles
Jakub Konecný
FedML
21
62
0
08 Mar 2021
Personalized Federated Learning using Hypernetworks
Personalized Federated Learning using Hypernetworks
Aviv Shamsian
Aviv Navon
Ethan Fetaya
Gal Chechik
FedML
27
324
0
08 Mar 2021
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned
  Data
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data
Runhua Xu
Nathalie Baracaldo
Yi Zhou
Ali Anwar
J. Joshi
Heiko Ludwig
FedML
10
75
0
05 Mar 2021
Evaluation and Optimization of Distributed Machine Learning Techniques
  for Internet of Things
Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of Things
Yansong Gao
Minki Kim
Chandra Thapa
Sharif Abuadbba
Zhi-Li Zhang
S. Çamtepe
Hyoungshick Kim
Surya Nepal
23
59
0
03 Mar 2021
Multi-institutional Collaborations for Improving Deep Learning-based
  Magnetic Resonance Image Reconstruction Using Federated Learning
Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning
Pengfei Guo
Puyang Wang
Jinyuan Zhou
Shanshan Jiang
Vishal M. Patel
FedML
OOD
36
143
0
03 Mar 2021
Towards Personalized Federated Learning
Towards Personalized Federated Learning
A. Tan
Han Yu
Li-zhen Cui
Qiang Yang
FedML
AI4CE
209
840
0
01 Mar 2021
Heterogeneity for the Win: One-Shot Federated Clustering
Heterogeneity for the Win: One-Shot Federated Clustering
D. Dennis
Tian Li
Virginia Smith
FedML
22
146
0
01 Mar 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
181
267
0
26 Feb 2021
Cybersecurity Threats in Connected and Automated Vehicles based
  Federated Learning Systems
Cybersecurity Threats in Connected and Automated Vehicles based Federated Learning Systems
Ranwa Al Mallah
Godwin Badu-Marfo
Bilal Farooq
29
19
0
26 Feb 2021
Emerging Trends in Federated Learning: From Model Fusion to Federated X
  Learning
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning
Shaoxiong Ji
Yue Tan
Teemu Saravirta
Zhiqin Yang
Yixin Liu
Lauri Vasankari
Shirui Pan
Guodong Long
A. Walid
FedML
37
76
0
25 Feb 2021
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
Amrith Rajagopal Setlur
Oscar Li
Virginia Smith
30
13
0
23 Feb 2021
Federated Evaluation and Tuning for On-Device Personalization: System
  Design & Applications
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications
Matthias Paulik
M. Seigel
Henry Mason
Dominic Telaar
Joris Kluivers
...
Dominic Hughes
O. Javidbakht
Fei Dong
Rehan Rishi
Stanley Hung
FedML
177
126
0
16 Feb 2021
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