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024 7 _a10.1007/978-981-19-8559-1
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082 0 4 _a005.13
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100 1 _aLü, Qingguo.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aDistributed Optimization in Networked Systems
_h[electronic resource] :
_bAlgorithms and Applications /
_cby Qingguo Lü, Xiaofeng Liao, Huaqing Li, Shaojiang Deng, Shanfu Gao.
250 _a1st ed. 2023.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2023.
300 _aXIX, 270 p. 1 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aWireless Networks,
_x2366-1445
505 0 _aChapter 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.
520 _aThis 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.
650 0 _aAlgorithms.
650 0 _aMachine learning.
650 0 _aComputer science.
650 1 4 _aDesign and Analysis of Algorithms.
650 2 4 _aMachine Learning.
650 2 4 _aTheory and Algorithms for Application Domains.
700 1 _aLiao, Xiaofeng.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aLi, Huaqing.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aDeng, Shaojiang.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aGao, Shanfu.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811985584
776 0 8 _iPrinted edition:
_z9789811985607
776 0 8 _iPrinted edition:
_z9789811985614
830 0 _aWireless Networks,
_x2366-1445
856 4 0 _uhttps://doi.org/10.1007/978-981-19-8559-1
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
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