Federated Edge Learning: Algorithms, Architectures by Yong Zhou(.PDF)+
File Size: 23.7 MB
Federated Edge Learning: Algorithms, Architectures and Trustworthiness (Wireless Networks) by Yong Zhou, Wenzhi Fang, Yuanming Shi, Khaled B. Letaief
Requirements: .ePUB, .PDF reader, 23.7 MB
Overview: This book presents various effective schemes from the perspectives of algorithms, architectures, privacy, and security to enable scalable and trustworthy Federated Edge Learning (FEEL). From the algorithmic perspective, the authors elaborate various federated optimization algorithms, including zeroth-order, first-order, and second-order methods. There is a specific emphasis on presenting provable convergence analysis to illustrate the impact of learning and wireless communication parameters. The convergence rate, computation complexity and communication overhead of the federated zeroth/first/second-order algorithms over wireless networks are elaborated. This book is designed for researchers and professionals whose focus is wireless communications. Advanced-level students majoring in computer science and electrical engineering will also find this book useful as a reference.
Genre: Non-Fiction > Tech & Devices
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