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Distributed Optimization in Networked Systems

Algorithms and Applications

Specificaties
Paperback, blz. | Engels
Springer Nature Singapore | e druk, 2024
ISBN13: 9789811985614
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Juridisch :
Springer Nature Singapore e druk, 2024 9789811985614
Onderdeel van serie Wireless Networks
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

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.

Specificaties

ISBN13:9789811985614
Taal:Engels
Bindwijze:paperback
Uitgever:Springer Nature Singapore

Inhoudsopgave

<p>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.<br></p>

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        Distributed Optimization in Networked Systems