£115.55

Springer Federated Learning Systems: Next-Generation AI Book

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Description

Federated Learning Systems: Towards Next-Generation AI offers a comprehensive look at the evolving landscape of distributed machine learning. As centralized training of deep learning models faces challenges like high communication costs for cloud data transfer and growing privacy protection concerns, this book provides necessary insights for the modern era of artificial intelligence. Published by Springer as part of the Studies in Computational Intelligence series, this text explores the research area through multiple lenses. Readers can explore bibliometric analysis, detailed reviews, empirical analysis, and various platforms. It is designed to help researchers and practitioners understand core issues in federated learning to help transform upcoming AI applications. By addressing the shift from centralized to distributed models, this work helps solve the problem of data privacy and communication efficiency in large-scale systems.

Key Features

Covers diverse research perspectives including bibliometric analysis, empirical studies, and reviews of current platforms.

Addresses critical challenges in centralized training such as high communication costs and data transfer issues to cloud systems.

Focuses on privacy protection concerns for data providers through the implementation of federated learning techniques.

Designed for both researchers and practitioners looking to understand the core issues of next-generation AI.

Part of the Studies in Computational Intelligence series (965) by Springer for academic and professional use.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
12 June 2021
Listed Since
28 January 2021

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No barcode data available

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