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Optimization Algorithms for Distributed Machine Learning

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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 di

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Optimization Algorithms for Distributed Machine Learning

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Barnes & Noble

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Barnes & Noble