VF-CART: A communication-efficient vertical federated framework for the CART algorithm
With growing concerns about privacy and the fact that data are distributed among multiple parties in realistic scenarios, vertical federated learning (VFL) is becoming increasingly important. There is an increasing trend in adapting machine learning algorithms to the VFL setting. As a category of pr...
Saved in:
| Main Authors: | Yang Xu, Xuexian Hu, Jianghong Wei, Hongjian Yang, Kejia Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2023-01-01
|
| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157822004116 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Efficient secure federated learning aggregation framework based on homomorphic encryption
by: Shengxing YU, et al.
Published: (2023-01-01) -
UniFL: Accelerating Federated Learning Using Heterogeneous Hardware Under a Unified Framework
by: Biyao Che, et al.
Published: (2024-01-01) -
HP_FLAP: homomorphic and polymorphic federated learning aggregation of parameters framework
by: Mohammad Moshawrab, et al.
Published: (2025-06-01) -
Recent advances of privacy-preserving machine learning based on (Fully) Homomorphic Encryption
by: Hong Cheng
Published: (2025-01-01) -
A privacy-preserving federated learning framework
by: Yang Dongning, et al.
Published: (2022-05-01)