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Combinatorial Reinforcement Learning Based Scheduling for DNN Execution on Edge
The past half-decade has seen unprecedented growth in machine learning with deep neural networks (DNNs) that represent state-of-the-art in many real-world applications.
Contrastive Weight Regularization for Large Minibatch SGD
The minibatch stochastic gradient descent method (SGD) is widely applied in deep learning due to its efficiency and scalability that enable training deep networks with a large volume of data.
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