Distributed Optimization in Networked Systems

Algorithms and Applications

Huaqing Li, Shanfu Gao, Qingguo Lü, et al.

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Springer Nature Singapore img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik

Beschreibung

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.

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Schlagwörter

Acceleration, Computational efficiency, Complex systems, Online learning, Distributed optimization, Networked systems, Smart grid applications, Privacy protection, Machine learning, Communication efficiency