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Federated Learning Fundamentals and Advances /

This book introduces readers to the fundamentals of and recent advances in federated learning, focusing on reducing communication costs, improving computational efficiency, and enhancing the security level. Federated learning is a distributed machine learning paradigm which enables model training on...

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Bibliographic Details
Main Authors: Jin, Yaochu (Author), Zhu, Hangyu (Author), Xu, Jinjin (Author), Chen, Yang (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Edition:1st ed. 2023.
Series:Machine Learning: Foundations, Methodologies, and Applications,
Subjects:
Machine learning.
Data protection > Law and legislation.
Cryptography.
Data encryption (Computer science).
Machine Learning.
Privacy.
Cryptology.
Online Access:https://doi.org/10.1007/978-981-19-7083-2
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Table of Contents:
  • Introduction
  • Communication-Efficient Federated Learning
  • Evolutionary Federated Learning.-Secure Federated Learning
  • Summary and Outlook.

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