<i>VFL-Cafe</i>: Communication-Efficient Vertical Federated Learning via Dynamic Caching and Feature Selection

<i>VFL-Cafe</i>: Communication-Efficient Vertical Federated Learning via Dynamic Caching and Feature Selection

Vertical Federated Learning (VFL) is a promising category of Federated Learning that enables collaborative model training among distributed parties with data privacy protection. Due to its unique training architecture, a key challenge of VFL is high communication cost due to transmitting intermediat...

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Bibliographic Details
Main Authors: Jiahui Zhou, Han Liang, Tian Wu, Xiaoxi Zhang, Yu Jiang, Chee Wei Tan
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Entropy
Subjects:
vertical federated learning
communication efficient
feature selection
dynamic caching
Online Access:https://www.mdpi.com/1099-4300/27/1/66
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