Vertical Federated Learning: A Structured Literature Review

By Afsana Khan et al

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Table of Contents

1. Introduction
2. Methodology
3. Research Results
3.1 Vertical Federated Learning
3.1.1 Communication
3.2 Improvements to Vertical Federated Learning

Summary

The paper discusses the emerging field of Vertical Federated Learning (VFL) and its potential applications in privacy-preserving machine learning. It provides a structured literature review focusing on the challenges, methodologies, and future directions in VFL. The study analyzes 97 articles related to VFL, highlighting the growth of research in this area since 2019. Key topics covered include different architectures for VFL, communication efficiency in multi-party settings, and improvements to enhance the learning process. Overall, the paper showcases the importance of VFL in addressing privacy concerns while enabling collaborative machine learning across organizations.