TY  - BOOK
AU  - Lü,Qingguo
AU  - Liao,Xiaofeng
AU  - Li,Huaqing
AU  - Deng,Shaojiang
AU  - Gao,Shanfu
ED  - SpringerLink (Online service)
TI  - Distributed Optimization in Networked Systems: Algorithms and Applications 
T2  - Wireless Networks,
SN  - 9789811985591
AV  - QA9.58 
U1  - 005.13 23
PY  - 2023///
CY  - Singapore
PB  - Springer Nature Singapore, Imprint: Springer
KW  - Algorithms
KW  - Machine learning
KW  - Computer science
KW  - Design and Analysis of Algorithms
KW  - Machine Learning
KW  - Theory and Algorithms for Application Domains
N1  - Acceso multiusuario; Chapter 1. Distributed Nesterov-Like Accelerated Algorithms in Networked Systems with Directed Communications -- Chapter 2. Distributed Stochastic Projected Gradient Algorithms for Composite Constrained Optimization in Networked Systems -- Chapter 3. Distributed Proximal Stochastic Gradient Algorithms for Coupled Composite Optimization in Networked Systems -- Chapter 4. Distributed Subgradient Algorithms Based on Event-Triggered Strategy in Networked Systems -- Chapter 5. Distributed Accelerated Stochastic Algorithms Based on Event-Triggered Strategy in Networked Systems -- Chapter 6. Event-Triggered Based Distributed Optimal Economic Dispatch in Smart Grids -- Chapter 7. Fast Distributed Optimal Economic Dispatch in Dynamic Smart Grids with Directed Communications -- Chapter 8. Accelerated Distributed Optimal Economic Dispatch in Smart Grids with Directed Communications -- Chapter 9. Privacy Preserving Distributed Online Learning with Time-Varying and Directed Communications
N2  - 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
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-19-8559-1
ER  -