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. 2305.12652
  4. Cited By
Privet: A Privacy-Preserving Vertical Federated Learning Service for
  Gradient Boosted Decision Tables
v1v2 (latest)

Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables

22 May 2023
Yifeng Zheng
Shuangqing Xu
Songlei Wang
Yan Gao
Zhongyun Hua
    FedML
ArXiv (abs)PDFHTML

Papers citing "Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables"

14 / 14 papers shown
Title
Federated Boosted Decision Trees with Differential Privacy
Federated Boosted Decision Trees with Differential Privacy
Samuel Maddock
Graham Cormode
Tianhao Wang
Carsten Maple
S. Jha
FedML
80
30
0
06 Oct 2022
OpBoost: A Vertical Federated Tree Boosting Framework Based on
  Order-Preserving Desensitization
OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization
Xiaochen Li
Yuke Hu
Weiran Liu
Hanwen Feng
Li Peng
Yuan Hong
Kui Ren
Zhan Qin
FedML
171
27
0
04 Oct 2022
CAFE: Catastrophic Data Leakage in Vertical Federated Learning
CAFE: Catastrophic Data Leakage in Vertical Federated Learning
Xiao Jin
Pin-Yu Chen
Chia-Yi Hsu
Chia-Mu Yu
Tianyi Chen
FedML
71
151
0
26 Oct 2021
CrypTen: Secure Multi-Party Computation Meets Machine Learning
CrypTen: Secure Multi-Party Computation Meets Machine Learning
Brian Knott
Shobha Venkataraman
Awni Y. Hannun
Shubho Sengupta
Mark Ibrahim
Laurens van der Maaten
92
361
0
02 Sep 2021
Privacy-Preserving Training of Tree Ensembles over Continuous Data
Privacy-Preserving Training of Tree Ensembles over Continuous Data
Samuel Adams
Chaitali Choudhary
Martine De Cock
Rafael Dowsley
David Melanson
Anderson C. A. Nascimento
Davis Railsback
Jianwei Shen
49
20
0
05 Jun 2021
An Efficient Learning Framework For Federated XGBoost Using Secret
  Sharing And Distributed Optimization
An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization
Lunchen Xie
Jiaqi Liu
Songtao Lu
Tsung-Hui Chang
Qingjiang Shi
FedML
56
38
0
12 May 2021
CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU
CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU
Sijun Tan
Brian Knott
Yuan Tian
David J. Wu
BDLFedML
91
193
0
22 Apr 2021
FederBoost: Private Federated Learning for GBDT
FederBoost: Private Federated Learning for GBDT
Zhihua Tian
Rui Zhang
Xiaoyang Hou
Jian Liu
K. Ren
Jian Liu
Kui Ren
FedMLAI4CE
98
68
0
05 Nov 2020
Privacy Preserving Vertical Federated Learning for Tree-based Models
Privacy Preserving Vertical Federated Learning for Tree-based Models
Yuncheng Wu
Shaofeng Cai
Xiaokui Xiao
Gang Chen
Beng Chin Ooi
FedML
44
213
0
14 Aug 2020
Large-Scale Secure XGB for Vertical Federated Learning
Large-Scale Secure XGB for Vertical Federated Learning
Wenjing Fang
Derun Zhao
Jin Tan
Chaochao Chen
Chaofan Yu
L. xilinx Wang
Lei Wang
Jun Zhou
Benyu Zhang
FedML
72
55
0
18 May 2020
Practical Federated Gradient Boosting Decision Trees
Practical Federated Gradient Boosting Decision Trees
Yue Liu
Zeyi Wen
Bingsheng He
FedMLAI4CE
119
193
0
11 Nov 2019
SecureBoost: A Lossless Federated Learning Framework
SecureBoost: A Lossless Federated Learning Framework
Kewei Cheng
Tao Fan
Yilun Jin
Yang Liu
Tianjian Chen
Dimitrios Papadopoulos
Qiang Yang
FedML
105
584
0
25 Jan 2019
Chameleon: A Hybrid Secure Computation Framework for Machine Learning
  Applications
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications
M. Riazi
Christian Weinert
Oleksandr Tkachenko
Ebrahim M. Songhori
T. Schneider
F. Koushanfar
FedML
48
495
0
10 Jan 2018
XGBoost: A Scalable Tree Boosting System
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
817
39,062
0
09 Mar 2016
1