Optimization Algorithms for Distributed Machine Learning (Synthesis Lectures on Learning, Networks, and Algorithms)

Joshi, Gauri

ISBN 10: 3031190661 / ISBN 13: 9783031190667

Published by Springer, 2022

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Bibliographic Details

• Title: Optimization Algorithms for Distributed Machine Learning (Synthesis Lectures on Learning, Networks, and Algorithms)
• Publisher: Springer
• Publication Date: 2022
• Language: English
• ISBN 10: 3031190661
• ISBN 13: 9783031190667
• Binding: Hardcover
• Condition: New

About this title

Synopsis

This book discusses state-of-the-art stochastic optimization algorithms for distributed machine learning and analyzes their convergence speed. The book first introduces stochastic gradient descent (SGD) and its distributed version, synchronous SGD, where the task of computing gradients is divided across several worker nodes. The author discusses several algorithms that improve the scalability and communication efficiency of synchronous SGD, such as asynchronous SGD, local-update SGD, quantized and sparsified SGD, and decentralized SGD....

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