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. 2207.11836
  4. Cited By
Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings
  through Graph Contrastive Learning

Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings through Graph Contrastive Learning

24 July 2022
Haoran Yang
Xiangyu Zhao
Muyang Li
Hongxu Chen
Guandong Xu
    FedML
ArXivPDFHTML

Papers citing "Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings through Graph Contrastive Learning"

2 / 2 papers shown
Title
Gromov-Wasserstein Discrepancy with Local Differential Privacy for
  Distributed Structural Graphs
Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs
Hongwei Jin
Xun Chen
25
9
0
01 Feb 2022
FedML: A Research Library and Benchmark for Federated Machine Learning
FedML: A Research Library and Benchmark for Federated Machine Learning
Chaoyang He
Songze Li
Jinhyun So
Xiao Zeng
Mi Zhang
...
Yang Liu
Ramesh Raskar
Qiang Yang
M. Annavaram
Salman Avestimehr
FedML
162
564
0
27 Jul 2020
1