Titlebook: Distributed Optimization in Networked Systems; Algorithms and Appli Qingguo Lü,Xiaofeng Liao,Shanfu Gao Book 2023 The Editor(s) (if applica

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https://doi.org/10.1007/978-981-19-8559-1Distributed optimization; Networked systems; Acceleration; Communication efficiency; Computational effic

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978-981-19-8561-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

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https://doi.org/10.1057/9780230253001-smooth regularization terms (. norm) subject to locally general constraints. Each of the smooth objective functions is further thought of as the average of several constituent functions, which is motivated by the modern large-scale information processing problems in machine learning (the samples of

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https://doi.org/10.1057/9780230253001 of several constituent functions, and the network aims to minimize a finite sum of all local functions plus a coupling function (possibly non-smooth). Due to its benefits in scalability, robustness, and flexibility, distributed optimization has been a significant focus in engineering research to ta