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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.
Published by: Springer
Publication Date: 2023-02-09
Format: Hardcover
ISBN-13: 9789811985584
DOI: 10.1007/978-981-19-8559-1
Dimensions: 235cm x155cm
Pages: 270