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PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient
  Push with Tight Utility Bounds

PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds

4 May 2024
Zehan Zhu
Yan Huang
Xin Wang
Jinming Xu
ArXivPDFHTML

Papers citing "PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds"

2 / 2 papers shown
Title
LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for
  Distributed Learning
LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning
Hsin-Pai Cheng
P. Yu
Haojing Hu
Feng Yan
Shiyu Li
Hai Helen Li
Yiran Chen
FedML
32
23
0
27 Nov 2018
Adaptive Federated Learning in Resource Constrained Edge Computing
  Systems
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang
Tiffany Tuor
Theodoros Salonidis
K. Leung
C. Makaya
T. He
Kevin S. Chan
144
1,687
0
14 Apr 2018
1