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Mobile edge artificial intelligenceopportunities and challenges /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mobile edge artificial intelligenceYuanming Shi, Kai Yang, Zhanpeng Yang, Yong Zhou.
Reminder of title:	opportunities and challenges /
Author:	Shi, Yuanming.
other author:	Yang, Kai.
Published:	London, United Kingdom ;Academic Press, an imprint of Elsevier,2022.
Description:	1 online resource.
Subject:	Mobile computing.
Online resource:	https://www.sciencedirect.com/science/book/9780128238172
ISBN:	9780128238356 (electronic bk.)

Mobile edge artificial intelligenceopportunities and challenges /
Shi, Yuanming.

Mobile edge artificial intelligenceopportunities and challenges /[electronic resource] :Yuanming Shi, Kai Yang, Zhanpeng Yang, Yong Zhou. - London, United Kingdom ;Academic Press, an imprint of Elsevier,2022. - 1 online resource.

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.

ISBN: 9780128238356 (electronic bk.)

Nat. Bib. No.: GBC1J6018bnbSubjects--Topical Terms:

185560
Mobile computing.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: QA76.59 / .S55 2021

Dewey Class. No.: 004.167

Mobile edge artificial intelligenceopportunities and challenges /
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245 1 0 $a Mobile edge artificial intelligence $h [electronic resource] : $b opportunities and challenges / $c Yuanming Shi, Kai Yang, Zhanpeng Yang, Yong Zhou.
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300 $a 1 online resource.
505 0 $a 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.
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700 1 $a Yang, Kai. $3 247629
700 1 $a Yang, Zhanpeng. $3 928241
700 1 $a Zhou, Yong. $3 522381
856 4 0 $u https://www.sciencedirect.com/science/book/9780128238172