£84.99

Elsevier Federated Learning: Theory and Practice

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Description

Federated Learning: Theory and Practi ce provides a holisti c treatment to federated learning as a distributed learning system with various forms of decentralized data and features. Part I of the book begins with a broad overview of opti mizati on fundamentals and modeling challenges, covering various aspects of communicati on effi ciency, theoretical convergence, and security. Part II features emerging challenges stemming from many socially driven concerns of federated learning as a future public machine learning service. Part III concludes the book with a wide array of industrial applicati ons of federated learning, as well as ethical considerations, showcasing its immense potential for driving innovation while safeguarding sensitive data. Federated Learning: Theory and Practi ce provides a comprehensive and accessible introducti on to federated learning which is suitable for researchers and students in academia, and industrial practitioners who seek to leverage the latest advance in machine learning for their entrepreneurial endeavors. Presents the fundamentals and a survey of key developments in the field of federated learning Provides emerging, state-of-the art topics that build on fundamentals Contains industry applications Gives an overview of visions of the future

Key Features

Federated Learning: Theory and Practice

Product_Type: ABIS_BOOK

Brand: Academic Press

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
29 March 2024
Listed Since
24 May 2023

Barcode

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