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.
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.
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.
Inhaltsangabe
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.
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.
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