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investigate and develop adaptive techniques for selecting hyperparameters, in order to reduce the tuning effort. For instance, the stochastic Polyak step size and its recent variants have shown promising
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. The reason is the overhead caused by specific hardware we use to train or execute neural networks. To make deep learning algorithms efficient in real life it is important to combine software and hardware
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