Abstract: Distributed training is the most common way to scale out and accelerate Deep Neural Network (DNN) training. Distributed DNN training requires synchronization of gradient aggregation among ...
Abstract: The fine scheduling of smart grids requires higher accuracy and robustness in bus load forecasting. Traditional methods, due to the fragmentation of multi-source data and insufficient model ...
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