Fr. 110.00

Edge Learning for Distributed Big Data Analytics - Theory, Algorithms, and System Design

English · Hardback

Shipping usually within 1 to 3 weeks (not available at short notice)

Description

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Introduces fundamental theory, basic and advanced algorithms, and system design issues. Essential for researchers and developers.

List of contents










1. Introduction; 2. Preliminary; 3. Fundamental Theory and Algorithms of Edge Learning; 4. Communication-Efficient Edge Learning; 5. Computation Acceleration; 6. Efficient Training with Heterogeneous Data Distribution; 7. Security and Privacy Issues in Edge Learning Systems; 8. Edge Learning Architecture Design for System Scalability; 9. Incentive Mechanisms in Edge Learning Systems; 10. Edge Learning Applications.

About the author

Song Guo is a Full Professor in the Department of Computing at The Hong Kong Polytechnic University. He is an IEEE Fellow and the Editor-in-Chief of the IEEE Open Journal of the Computer Society. He was a member of the IEEE ComSoc Board of Governors and a Distinguished Lecturer of the IEEE Communications Society.Zhihao Qu is an assistant researcher in the School of Computer and Information at Hohai University and in the Department of Computing at The Hong Kong Polytechnic University.

Summary

Introduces fundamental theory, basic and advanced algorithms, and system design issues. Essential reading for experienced researchers and developers, or for those who are just entering the field.

Foreword

Introduces fundamental theory, basic and advanced algorithms, and system design issues. Essential for researchers and developers.

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