Książka Optimization Algorithms for Distributed Machine Learning Gauri Joshi

Optimization Algorithms for Distributed Machine Learning

Autor: Gauri Joshi
Język: Angielski
Oprawa: Miękka
Wydawca: Springer, Berlin
Dostępność: Dostępna u dostawcy
Wysyłamy za 5-8 dni
186.95
This book discusses state-of-the-art stochastic optimization algorithms for distributed machine lear...

Informacje o książce

Autor
Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2023
strony
127
EAN
9783031190698
Enbook ID
44406882
Waga
240
Wymiary
168 x 240

Pełny opis

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.

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