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Explore the concepts, algorithms, and applications underlying federated learning
In Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering federated learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects federated learning performance, accuracy, convergence, scalability, and security and privacy.
Readers will explore a wide range of topics that show how federated learning algorithms, concepts, and design and optimization issues apply to wireless communications. Readers will also find:
Perfect for electrical and computer science engineers, researchers, professors, and postgraduate students with an interest in machine learning, Federated Learning for Future Intelligent Wireless Networks will also benefit regulators and institutional actors responsible for overseeing and making policy in the area of artificial intelligence.
Author: Yao Sun
ISBN-10: 1119913896
ISBN-13: 9781119913894
Publisher: Wiley-IEEE Press
Language: English
Published: 12/27/2023
Pages: 320
Format: Hardcover
Weight: 1.30lbs
Size: 9.00h x 6.00w x 0.75d
Yao Sun, PhD, is a Lecturer with the University of Glasgow in the United Kingdom. He was a former Research Fellow at UESTC in Chengdu, China.
Chaoqun You is a Research Fellow at the Singapore University of Technology and Design. She was formerly an Academic Guest with the Department of Electronic Computer Engineering at the University of Toronto.
Gang Feng is a Professor at the University of Electronic Science and Technology of China. He was an Associate Professor at Nanyang Technological University.
Lei Zhang, PhD, is a Professor at the University of Glasgow, UK. He was formerly a Research Fellow at the 5G Innovation Centre at the University of Surrey.
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