Titlebook: Optimization Algorithms for Distributed Machine Learning; Gauri Joshi Book 2023 The Editor(s) (if applicable) and The Author(s), under exc

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Gauri Joshil applicability. This book presents a formal treatment of some aspects of control theory applied to the problem of vision-based pose regulation of wheeled mobile robots. In this problem, the robot has to reach a desired position and orientation, which are specified by a target image. It is faced in

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,Asynchronous SGD and Staleness-Reduced Variants,atch-sync SGD overcome the straggling delay, but they end up discarding partially completed gradient computation at one or more workers, thus reducing the statistical efficiency of the algorithm and adversely affecting the error convergence.

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Synthesis Lectures on Learning, Networks, and Algorithmshttp://image.papertrans.cn/o/image/703136.jpg

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https://doi.org/10.1007/978-3-031-19067-4Distributed Machine Learning; Distributed Optimization; Optimization Algorithms; Stochastic Gradient De

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,Distributed Optimization in Machine Learning,Machine learning is revolutionizing data-driven decision-making in a myriad applications including search and recommendations, self-driving cars, robotics, and medical diagnosis.

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,Calculus, Probability and Order Statistics Review,In this chapter, we will begin by reviewing some concepts from calculus and probability that are essential to understanding the error and runtime analyses of various distributed SGD algorithms that we will study in the rest of the book.