Secure and Efficient Federated Gradient Boosting Decision Trees
In recent years, federated GBDTs have gradually replaced traditional GBDTs, and become the focus of academic research. They are used to solve the task of structured data mining. Aiming at the problems of information leakage, insufficient model accuracy and high communication cost in the existing sch...
Main Authors: | Xue Zhao, Xiaohui Li, Shuang Sun, Xu Jia |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-03-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/7/4283 |
Similar Items
-
eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees
by: Fuki Yamamoto, et al.
Published: (2022-01-01) -
FedVoting: A Cross-Silo Boosting Tree Construction Method for Privacy-Preserving Long-Term Human Mobility Prediction
by: Yinghao Liu, et al.
Published: (2021-12-01) -
A method for modelling greenhouse temperature using gradient boost decision tree
by: Wentao Cai, et al.
Published: (2022-09-01) -
iEnhancer-MFGBDT: Identifying enhancers and their strength by fusing multiple features and gradient boosting decision tree
by: Yunyun Liang, et al.
Published: (2021-10-01) -
Computational Prediction of Critical Temperatures of Superconductors Based on Convolutional Gradient Boosting Decision Trees
by: Yabo Dan, et al.
Published: (2020-01-01)