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. 2112.04261
  4. Cited By
Efficient Batch Homomorphic Encryption for Vertically Federated XGBoost

Efficient Batch Homomorphic Encryption for Vertically Federated XGBoost

8 December 2021
Wuxing Xu
Hao Fan
Kaixin Li
Kairan Yang
    FedML
ArXivPDFHTML

Papers citing "Efficient Batch Homomorphic Encryption for Vertically Federated XGBoost"

2 / 2 papers shown
Title
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
76
162
0
23 Nov 2022
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
1,713
0
18 Mar 2020
1