ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2209.00230
  4. Cited By
Trading Off Privacy, Utility and Efficiency in Federated Learning

Trading Off Privacy, Utility and Efficiency in Federated Learning

1 September 2022
Xiaojin Zhang
Yan Kang
Kai Chen
Lixin Fan
Qiang Yang
    FedML
ArXivPDFHTML

Papers citing "Trading Off Privacy, Utility and Efficiency in Federated Learning"

13 / 13 papers shown
Title
Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning
Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning
Shunxin Guo
Jiaqi Lv
Xin Geng
49
0
0
27 Apr 2025
Federated Continual Learning via Knowledge Fusion: A Survey
Federated Continual Learning via Knowledge Fusion: A Survey
Xin Yang
Hao Yu
Xin Gao
Hao Wang
Junbo Zhang
Tianrui Li
FedML
41
33
0
27 Dec 2023
A Survey for Federated Learning Evaluations: Goals and Measures
A Survey for Federated Learning Evaluations: Goals and Measures
Di Chai
Leye Wang
Liu Yang
Junxue Zhang
Kai Chen
Qian Yang
ELM
FedML
27
21
0
23 Aug 2023
A Survey of What to Share in Federated Learning: Perspectives on Model
  Utility, Privacy Leakage, and Communication Efficiency
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency
Jiawei Shao
Zijian Li
Wenqiang Sun
Tailin Zhou
Yuchang Sun
Lumin Liu
Zehong Lin
Yuyi Mao
Jun Zhang
FedML
45
23
0
20 Jul 2023
Theoretically Principled Federated Learning for Balancing Privacy and
  Utility
Theoretically Principled Federated Learning for Balancing Privacy and Utility
Xiaojin Zhang
Wenjie Li
Kai Chen
Shutao Xia
Qian Yang
FedML
30
9
0
24 May 2023
A Game-theoretic Framework for Privacy-preserving Federated Learning
A Game-theoretic Framework for Privacy-preserving Federated Learning
Xiaojin Zhang
Lixin Fan
Si-Yi Wang
Wenjie Li
Kai Chen
Qiang Yang
FedML
31
4
0
11 Apr 2023
FedPass: Privacy-Preserving Vertical Federated Deep Learning with
  Adaptive Obfuscation
FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation
Hanlin Gu
Jiahuan Luo
Yan Kang
Lixin Fan
Qiang Yang
FedML
36
13
0
30 Jan 2023
Vertical Federated Learning: Concepts, Advances and Challenges
Vertical Federated Learning: Concepts, Advances and Challenges
Yang Liu
Yan Kang
Tianyuan Zou
Yanhong Pu
Yuanqin He
Xiaozhou Ye
Ye Ouyang
Yaqin Zhang
Qian Yang
FedML
64
162
0
23 Nov 2022
A Framework for Evaluating Privacy-Utility Trade-off in Vertical
  Federated Learning
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning
Yan Kang
Jiahuan Luo
Yuanqin He
Xiaojin Zhang
Lixin Fan
Qiang Yang
FedML
19
15
0
08 Sep 2022
Federated Deep Learning with Bayesian Privacy
Federated Deep Learning with Bayesian Privacy
Hanlin Gu
Lixin Fan
Bowen Li Jie Li
Yan Kang
Yuan Yao
Qiang Yang
FedML
88
24
0
27 Sep 2021
Label Leakage and Protection in Two-party Split Learning
Label Leakage and Protection in Two-party Split Learning
Oscar Li
Jiankai Sun
Xin Yang
Weihao Gao
Hongyi Zhang
Junyuan Xie
Virginia Smith
Chong-Jun Wang
FedML
134
139
0
17 Feb 2021
The Future of Digital Health with Federated Learning
The Future of Digital Health with Federated Learning
Nicola Rieke
Jonny Hancox
Wenqi Li
Fausto Milletari
H. Roth
...
Ronald M. Summers
Andrew Trask
Daguang Xu
Maximilian Baust
M. Jorge Cardoso
OOD
174
1,712
0
18 Mar 2020
Privacy Against Statistical Inference
Privacy Against Statistical Inference
Flavio du Pin Calmon
N. Fawaz
FedML
100
345
0
08 Oct 2012
1