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. 2407.16735
  4. Cited By
Theoretical Analysis of Privacy Leakage in Trustworthy Federated
  Learning: A Perspective from Linear Algebra and Optimization Theory

Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory

23 July 2024
Xiaojin Zhang
Wei Chen
    FedML
ArXivPDFHTML

Papers citing "Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory"

1 / 1 papers shown
Title
Reinforcement Learning as a Catalyst for Robust and Fair Federated
  Learning: Deciphering the Dynamics of Client Contributions
Reinforcement Learning as a Catalyst for Robust and Fair Federated Learning: Deciphering the Dynamics of Client Contributions
Jialuo He
Wei Chen
Xiaojin Zhang
FedML
AAML
22
1
0
08 Feb 2024
1