Federated Learning
Language: English
Published by Springer International Publishing AG, CH, 2019
Series: Book 13 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
- New
Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
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Add to basketItem description from seller
Seller Inventory # LU-9783031004575
- Title
- Federated Learning
- Author
- Qiang Yang, Yang Liu, Yong Cheng, Yan Kang, Tianjian Chen, Han Yu
- Publisher
- Springer International Publishing AG, CH
- Publication year
- 2019
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 3031004574
- ISBN 13
- 9783031004575
- Series
- Book 13 of 14: Synthesis Lectures on Artificial Intelligence and Machine Learning
How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private?
Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.
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