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Differentially Private Federated Learning: A Client Level Perspective

Differentially Private Federated Learning: A Client Level Perspective

20 December 2017
Robin C. Geyer
T. Klein
Moin Nabi
    FedML
ArXivPDFHTML

Papers citing "Differentially Private Federated Learning: A Client Level Perspective"

50 / 233 papers shown
Title
Improving Federated Learning Face Recognition via Privacy-Agnostic
  Clusters
Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters
Qiang Meng
Feng Zhou
Hainan Ren
Tianshu Feng
Guochao Liu
Yuanqing Lin
FedML
33
38
0
29 Jan 2022
A Secure and Efficient Federated Learning Framework for NLP
A Secure and Efficient Federated Learning Framework for NLP
Jieren Deng
Chenghong Wang
Xianrui Meng
Yijue Wang
Ji Li
Sheng Lin
Shuo Han
Fei Miao
Sanguthevar Rajasekaran
Caiwen Ding
FedML
77
22
0
28 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
73
0
19 Jan 2022
Feature Space Hijacking Attacks against Differentially Private Split
  Learning
Feature Space Hijacking Attacks against Differentially Private Split Learning
Grzegorz Gawron
P. Stubbings
AAML
27
20
0
11 Jan 2022
Gradient Leakage Attack Resilient Deep Learning
Gradient Leakage Attack Resilient Deep Learning
Wenqi Wei
Ling Liu
SILM
PILM
AAML
29
47
0
25 Dec 2021
The Impact of Data Distribution on Fairness and Robustness in Federated
  Learning
The Impact of Data Distribution on Fairness and Robustness in Federated Learning
Mustafa Safa Ozdayi
Murat Kantarcioglu
FedML
OOD
24
4
0
29 Nov 2021
Non-IID data and Continual Learning processes in Federated Learning: A
  long road ahead
Non-IID data and Continual Learning processes in Federated Learning: A long road ahead
Marcos F. Criado
F. Casado
R. Iglesias
Carlos V. Regueiro
S. Barro
FedML
38
77
0
26 Nov 2021
Differentially Private Federated Learning on Heterogeneous Data
Differentially Private Federated Learning on Heterogeneous Data
Maxence Noble
A. Bellet
Aymeric Dieuleveut
FedML
13
103
0
17 Nov 2021
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining
  Competitive Performance in Federated Learning
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
Yuezhou Wu
Yan Kang
Jiahuan Luo
Yuanqin He
Qiang Yang
FedML
AAML
19
69
0
16 Nov 2021
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning
Lokesh Nagalapatti
Mahdi S. Hosseini
FedML
30
75
0
23 Oct 2021
Federated Learning from Small Datasets
Federated Learning from Small Datasets
Michael Kamp
Jonas Fischer
Jilles Vreeken
FedML
32
26
0
07 Oct 2021
Fairness-Driven Private Collaborative Machine Learning
Fairness-Driven Private Collaborative Machine Learning
Dana Pessach
Tamir Tassa
E. Shmueli
FedML
33
7
0
29 Sep 2021
NanoBatch Privacy: Enabling fast Differentially Private learning on the
  IPU
NanoBatch Privacy: Enabling fast Differentially Private learning on the IPU
Edward H. Lee
M. M. Krell
Alexander Tsyplikhin
Victoria Rege
E. Colak
Kristen W. Yeom
FedML
21
0
0
24 Sep 2021
DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks
  in Federated Learning
DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks in Federated Learning
Md Tamjid Hossain
Shafkat Islam
S. Badsha
Haoting Shen
AAML
55
41
0
21 Sep 2021
Source Inference Attacks in Federated Learning
Source Inference Attacks in Federated Learning
Hongsheng Hu
Z. Salcic
Lichao Sun
Gillian Dobbie
Xuyun Zhang
27
79
0
13 Sep 2021
FedTriNet: A Pseudo Labeling Method with Three Players for Federated
  Semi-supervised Learning
FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning
Liwei Che
Zewei Long
Jiaqi Wang
Yaqing Wang
Houping Xiao
Fenglong Ma
FedML
27
23
0
12 Sep 2021
FedCon: A Contrastive Framework for Federated Semi-Supervised Learning
FedCon: A Contrastive Framework for Federated Semi-Supervised Learning
Zewei Long
Jiaqi Wang
Yaqing Wang
Houping Xiao
Fenglong Ma
FedML
48
22
0
09 Sep 2021
Private Multi-Task Learning: Formulation and Applications to Federated
  Learning
Private Multi-Task Learning: Formulation and Applications to Federated Learning
Shengyuan Hu
Zhiwei Steven Wu
Virginia Smith
FedML
27
19
0
30 Aug 2021
Order Optimal Bounds for One-Shot Federated Learning over non-Convex
  Loss Functions
Order Optimal Bounds for One-Shot Federated Learning over non-Convex Loss Functions
Arsalan Sharifnassab
Saber Salehkaleybar
S. J. Golestani
FedML
11
0
0
19 Aug 2021
Aggregation Delayed Federated Learning
Aggregation Delayed Federated Learning
Ye Xue
Diego Klabjan
Yuan Luo
FedML
OOD
28
5
0
17 Aug 2021
Dynamic Attention-based Communication-Efficient Federated Learning
Dynamic Attention-based Communication-Efficient Federated Learning
Zihan Chen
Kai Fong Ernest Chong
Tony Q.S. Quek
FedML
50
11
0
12 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Runhua Xu
Nathalie Baracaldo
J. Joshi
32
100
0
10 Aug 2021
Precision-Weighted Federated Learning
Precision-Weighted Federated Learning
Jonatan Reyes
Di-Jorio Lisa
Cécile Low-Kam
Marta Kersten-Oertel
FedML
16
35
0
20 Jul 2021
AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning
AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning
Young Geun Kim
Carole-Jean Wu
26
85
0
16 Jul 2021
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning
Paul Pu Liang
Yiwei Lyu
Xiang Fan
Zetian Wu
Yun Cheng
...
Peter Wu
Michelle A. Lee
Yuke Zhu
Ruslan Salakhutdinov
Louis-Philippe Morency
VLM
32
159
0
15 Jul 2021
Byzantine-robust Federated Learning through Spatial-temporal Analysis of
  Local Model Updates
Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates
Zhuohang Li
Luyang Liu
Jiaxin Zhang
Jian-Dong Liu
FedML
OOD
AAML
35
10
0
03 Jul 2021
Gradient-Leakage Resilient Federated Learning
Gradient-Leakage Resilient Federated Learning
Wenqi Wei
Ling Liu
Yanzhao Wu
Gong Su
Arun Iyengar
FedML
19
81
0
02 Jul 2021
Benchmarking Differential Privacy and Federated Learning for BERT Models
Benchmarking Differential Privacy and Federated Learning for BERT Models
Priya Basu
Tiasa Singha Roy
Rakshit Naidu
Zumrut Muftuoglu
Sahib Singh
Fatemehsadat Mireshghallah
FedML
AI4MH
24
50
0
26 Jun 2021
Understanding Clipping for Federated Learning: Convergence and
  Client-Level Differential Privacy
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy
Xinwei Zhang
Xiangyi Chen
Min-Fong Hong
Zhiwei Steven Wu
Jinfeng Yi
FedML
32
91
0
25 Jun 2021
Learning Language and Multimodal Privacy-Preserving Markers of Mood from
  Mobile Data
Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data
Paul Pu Liang
Terrance Liu
Anna Cai
Michal Muszynski
Ryo Ishii
Nicholas B. Allen
Randy P. Auerbach
David Brent
Ruslan Salakhutdinov
Louis-Philippe Morency
38
16
0
24 Jun 2021
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
Chulin Xie
Minghao Chen
Pin-Yu Chen
Bo-wen Li
FedML
36
165
0
15 Jun 2021
Differentially Private Federated Knowledge Graphs Embedding
Differentially Private Federated Knowledge Graphs Embedding
Hao Peng
Haoran Li
Yangqiu Song
V. Zheng
Jianxin Li
FedML
36
80
0
17 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
30
87
0
04 May 2021
Citadel: Protecting Data Privacy and Model Confidentiality for
  Collaborative Learning with SGX
Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX
Chengliang Zhang
Junzhe Xia
Baichen Yang
Huancheng Puyang
Wei Wang
Ruichuan Chen
Istemi Ekin Akkus
Paarijaat Aditya
Feng Yan
FedML
53
39
0
04 May 2021
Privacy-Preserving Federated Learning on Partitioned Attributes
Privacy-Preserving Federated Learning on Partitioned Attributes
Shuang Zhang
Liyao Xiang
Xi Yu
Pengzhi Chu
Yingqi Chen
Chen Cen
L. Wang
FedML
28
2
0
29 Apr 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
56
244
0
29 Apr 2021
A Graph Federated Architecture with Privacy Preserving Learning
A Graph Federated Architecture with Privacy Preserving Learning
Elsa Rizk
Ali H. Sayed
FedML
39
21
0
26 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
31
44
0
21 Apr 2021
A Joint Energy and Latency Framework for Transfer Learning over 5G
  Industrial Edge Networks
A Joint Energy and Latency Framework for Transfer Learning over 5G Industrial Edge Networks
Bofu Yang
Omobayode Fagbohungbe
Xuelin Cao
Chau Yuen
Lijun Qian
Dusit Niyato
Yan Zhang
39
31
0
19 Apr 2021
The Role of Cross-Silo Federated Learning in Facilitating Data Sharing
  in the Agri-Food Sector
The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector
A. Durrant
Milan Markovic
David Matthews
David May
J. Enright
Georgios Leontidis
FedML
32
69
0
14 Apr 2021
Privacy-preserving Federated Learning based on Multi-key Homomorphic
  Encryption
Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption
Jing Ma
Si-Ahmed Naas
S. Sigg
X. Lyu
29
245
0
14 Apr 2021
Federated Learning with Taskonomy for Non-IID Data
Federated Learning with Taskonomy for Non-IID Data
Hadi Jamali Rad
Mohammad Abdizadeh
Anuj Singh
FedML
48
54
0
29 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
35
412
0
14 Mar 2021
Private Cross-Silo Federated Learning for Extracting Vaccine Adverse
  Event Mentions
Private Cross-Silo Federated Learning for Extracting Vaccine Adverse Event Mentions
Pallika H. Kanani
Virendra J. Marathe
Daniel W. Peterson
R. Harpaz
Steve Bright
FedML
16
9
0
12 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
13
75
0
05 Mar 2021
Privacy Amplification for Federated Learning via User Sampling and
  Wireless Aggregation
Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation
Mohamed Seif
Wei-Ting Chang
Ravi Tandon
FedML
26
45
0
02 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
189
268
0
26 Feb 2021
Federated Learning with Local Differential Privacy: Trade-offs between
  Privacy, Utility, and Communication
Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communication
Muah Kim
Onur Gunlu
Rafael F. Schaefer
FedML
110
118
0
09 Feb 2021
Federated Learning on Non-IID Data Silos: An Experimental Study
Federated Learning on Non-IID Data Silos: An Experimental Study
Yue Liu
Yiqun Diao
Quan Chen
Bingsheng He
FedML
OOD
101
955
0
03 Feb 2021
Federated Multi-Armed Bandits
Federated Multi-Armed Bandits
Chengshuai Shi
Cong Shen
FedML
63
92
0
28 Jan 2021
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