Federated Learning Systems
Towards Next-Generation AI
Mohamed Medhat Gaber editor Muhammad Habib ur Rehman editor
Format:Paperback
Publisher:Springer Nature Switzerland AG
Published:12th Jun '22
Currently unavailable, and unfortunately no date known when it will be back
This paperback is available in another edition too:
- Hardback£129.99(9783030706036)
This book covers the research area from multiple viewpoints including bibliometric analysis, reviews, empirical analysis, platforms, and future applications. The centralized training of deep learning and machine learning models not only incurs a high communication cost of data transfer into the cloud systems but also raises the privacy protection concerns of data providers. This book aims at targeting researchers and practitioners to delve deep into core issues in federated learning research to transform next-generation artificial intelligence applications. Federated learning enables the distribution of the learning models across the devices and systems which perform initial training and report the updated model attributes to the centralized cloud servers for secure and privacy-preserving attribute aggregation and global model development. Federated learning benefits in terms of privacy, communication efficiency, data security, and contributors’ control of their critical data.
ISBN: 9783030706067
Dimensions: unknown
Weight: 332g
196 pages
1st ed. 2021