This book focuses on improving the performance (convergence rate, communication efficiency, computational efficiency, etc.) of algorithms in the context of distributed optimization in networked systems and their successful application to real-world applications (smart grids and online learning). Readers may be particularly interested in the sections on consensus protocols, optimization skills, accelerated mechanisms, event-triggered strategies, variance-reduction communication techniques, etc., in connection with distributed optimization in various networked systems. This book offers a valuable reference guide for researchers in distributed optimization and for senior undergraduate and graduate students alike.
| Autorius: | Qingguo Lü, Xiaofeng Liao, Shanfu Gao, Shaojiang Deng, Huaqing Li, |
| Serija: | Wireless Networks |
| Leidėjas: | Springer Nature Singapore |
| Išleidimo metai: | 2024 |
| Knygos puslapių skaičius: | 292 |
| ISBN-10: | 9811985618 |
| ISBN-13: | 9789811985614 |
| Formatas: | Knyga minkštu viršeliu |
| Kalba: | Anglų |
| Žanras: | Machine learning |
Parašykite atsiliepimą apie „Distributed Optimization in Networked Systems: Algorithms and Applications“
