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Time-Varying Convex Optimization Time-Structured Algorithms and Applications

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Document pages: 14 pages

Abstract: Optimization underpins many of the challenges that science and technologyface on a daily basis. Recent years have witnessed a major shift fromtraditional optimization paradigms grounded on batch algorithms formedium-scale problems to challenging dynamic, time-varying, and even huge-sizesettings. This is driven by technological transformations that convertedinfrastructural and social platforms into complex and dynamic networked systemswith even pervasive sensing and computing capabilities. The present paperreviews a broad class of state-of-the-art algorithms for time-varyingoptimization, with an eye to both algorithmic development and performanceanalysis. It offers a comprehensive overview of available tools and methods,and unveils open challenges in application domains of broad interest. Thereal-world examples presented include smart power systems, robotics, machinelearning, and data analytics, highlighting domain-specific issues andsolutions. The ultimate goal is to exempify wide engineering relevance ofanalytical tools and pertinent theoretical foundations.

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