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Full Description
Mobile Edge Artificial Intelligence: Opportunities and Challenges presents recent advances in wireless technologies and nonconvex optimization techniques for designing efficient edge AI systems. The book includes comprehensive coverage on modeling, algorithm design and theoretical analysis. Through typical examples, the powerfulness of this set of systems and algorithms is demonstrated, along with their abilities to make low-latency, reliable and private intelligent decisions at network edge. With the availability of massive datasets, high performance computing platforms, sophisticated algorithms and software toolkits, AI has achieved remarkable success in many application domains.
As such, intelligent wireless networks will be designed to leverage advanced wireless communications and mobile computing technologies to support AI-enabled applications at various edge mobile devices with limited communication, computation, hardware and energy resources.
Contents
I. Introduction and Overview
1. Primer on Artificial Intelligence
2. Overview of Edge AI Systems
II. Edge Inference
3. Model Compression for On-Device Inference
4. Wireless MapReduce for Device Distributed Inference
5. Wireless Cooperative Transmission for Edge Inference
III. Edge Training
6. Over-the-Air Computation for Federated Learning
7. Blind Over-the-Air Computation for Federated Learning
8. Reconfigurable Intelligent Surface Aided Federated Learning System
IV. Future Directions
9. Communication-Efficient Algorithms for Edge AI
10. Future Research Directions
