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Optimization Algorithms for Distributed Machine Learning (Synthesis Lectures on Learning, Networks, and Algorithms) - Softcover
- PublisherSpringer
- Publication date2023
- ISBN 10 3031190696
- ISBN 13 9783031190698
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages144
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Optimization Algorithms for Distributed Machine Learning (Synthesis Lectures on Learning, Networks, and Algorithms)
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Optimization Algorithms for Distributed Machine Learning (Synthesis Lectures on Learning, Networks, and Algorithms)
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Optimization Algorithms for Distributed Machine Learning
Published by
Springer International Publishing, Springer Nature Switzerland Nov 2023, 2023
ISBN 10: 3031190696
ISBN 13: 9783031190698
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. For each of these algorithms, the book analyzes its error versus iterations convergence, and the runtime spent per iteration. The author shows that each of these strategies to reduce communication or synchronization delays encounters a fundamental trade-off between error and runtime. 144 pp. Englisch. Seller Inventory # 9783031190698
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Optimization Algorithms for Distributed Machine Learning
Published by
Springer International Publishing, Springer Nature Switzerland, 2023
ISBN 10: 3031190696
ISBN 13: 9783031190698
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. For each of these algorithms, the book analyzes its error versus iterations convergence, and the runtime spent per iteration. The author shows that each of these strategies to reduce communication or synchronization delays encounters a fundamental trade-off between error and runtime. Seller Inventory # 9783031190698
Quantity: 1 available
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Optimization Algorithms for Distributed Machine Learning
Published by
Springer-Nature New York Inc, 2023
ISBN 10: 3031190696
ISBN 13: 9783031190698
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Paperback
Seller: Revaluation Books, Exeter, United Kingdom
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Paperback. Condition: Brand New. 140 pages. 9.45x6.61x0.33 inches. In Stock. Seller Inventory # x-3031190696
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Optimization Algorithms for Distributed Machine Learning
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Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10: 3031190696
ISBN 13: 9783031190698
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Kartoniert / Broschiert
Seller: moluna, Greven, Germany
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 th. Seller Inventory # 1215161127
Quantity: Over 20 available