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There is significant recent interest to parallelize deep learning algorithms in order to handle the enormous growth in data and model sizes.
Some methods of speeding up the convergence of iteration methods
Boris T Polyak · 1964
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Continuous trajectory planning of mobile sensors for informative forecasting
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A new class of distributed optimization algorithms: application to regression of distributed data
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Tensorflow: Large-scale machine learning on heterogeneous distributed systems
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