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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
ArXiv (abs)PDFHTML

Papers citing "Privacy-Preserving Training of Tree Ensembles over Continuous Data"

12 / 12 papers shown
Title
OnePath: Efficient and Privacy-Preserving Decision Tree Inference in the Cloud
OnePath: Efficient and Privacy-Preserving Decision Tree Inference in the Cloud
Shuai Yuan
Hongwei Li
Xinyuan Qian
Wenbo Jiang
Guowen Xu
36
0
0
28 Sep 2024
Ents: An Efficient Three-party Training Framework for Decision Trees by Communication Optimization
Ents: An Efficient Three-party Training Framework for Decision Trees by Communication Optimization
Guopeng Lin
Weili Han
Wenqiang Ruan
Ruisheng Zhou
Lushan Song
Bingshuai Li
Yunfeng Shao
73
2
0
12 Jun 2024
Eliminating Label Leakage in Tree-Based Vertical Federated Learning
Eliminating Label Leakage in Tree-Based Vertical Federated Learning
Hideaki Takahashi
Qingbin Liu
Yang Liu
AAMLFedML
87
5
0
19 Jul 2023
Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables
Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables
Yifeng Zheng
Shuangqing Xu
Songlei Wang
Yan Gao
Zhongyun Hua
FedML
87
10
0
22 May 2023
GTree: GPU-Friendly Privacy-preserving Decision Tree Training and Inference
GTree: GPU-Friendly Privacy-preserving Decision Tree Training and Inference
Qifan Wang
Shujie Cui
Lei Zhou
Ye Dong
Jianli Bai
Yun Sing Koh
Giovanni Russello
122
1
0
01 May 2023
Secure Multiparty Computation for Synthetic Data Generation from Distributed Data
Secure Multiparty Computation for Synthetic Data Generation from Distributed Data
Mayana Pereira
Sikha Pentyala
A. Nascimento
R. T. D. Sousa
Martine De Cock
44
6
0
13 Oct 2022
Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis
Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis
Shigehiko Schamoni
Michael Hagmann
Stefan Riezler
FedML
53
4
0
01 Sep 2022
Training Differentially Private Models with Secure Multiparty Computation
Training Differentially Private Models with Secure Multiparty Computation
Sikha Pentyala
Davis Railsback
Ricardo Maia
Rafael Dowsley
David Melanson
Anderson C. A. Nascimento
Martine De Cock
72
15
0
05 Feb 2022
Report: State of the Art Solutions for Privacy Preserving Machine Learning in the Medical Context
Report: State of the Art Solutions for Privacy Preserving Machine Learning in the Medical Context
J. Zalonis
Frederik Armknecht
Björn Grohmann
Manuel Koch
74
4
0
27 Jan 2022
Efficient decision tree training with new data structure for secure multi-party computation
Efficient decision tree training with new data structure for secure multi-party computation
Koki Hamada
Dai Ikarashi
Ryo Kikuchi
Koji Chida
40
12
0
24 Dec 2021
Round and Communication Balanced Protocols for Oblivious Evaluation of Finite State Machines
Round and Communication Balanced Protocols for Oblivious Evaluation of Finite State Machines
Rafael Dowsley
Caleb Horst
Anderson C. A. Nascimento
44
0
0
20 Mar 2021
Fast Privacy-Preserving Text Classification based on Secure Multiparty Computation
Fast Privacy-Preserving Text Classification based on Secure Multiparty Computation
A. Resende
Davis Railsback
Rafael Dowsley
Anderson C. A. Nascimento
Diego F. Aranha
65
21
0
18 Jan 2021