MMVFL: a simple vertical federated learning framework for multi-class multi-participant scenarios

MMVFL: a simple vertical federated learning framework for multi-class multi-participant scenarios

Federated learning (FL) is a privacy-preserving collective machine learning paradigm. Vertical federated learning (VFL) deals with the case where participants share the same sample ID space but have different feature spaces, while label information is owned by one participant. Early studies of VFL s...

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Bibliographic Details
Main Authors: Feng, Siwei, Yu, Han, Zhu, Yuebing
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2024
Subjects:
Computer and Information Science
Vertical federated learning
Multiple participants
Online Access:https://hdl.handle.net/10356/178634

Internet

https://hdl.handle.net/10356/178634

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