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Applying Cyclical Learning Rate to Neural Machine Translation
In training deep learning networks, the optimizer and related learning rate are often used without much thought or with minimal tuning, even though it is crucial in ensuring a fast convergence to a good quality minimum of the loss function that can also generalize well on the test dataset.
Practical Matrix Completion and Corruption Recovery using Proximal Alternating Robust Subspace Minimization
Low-rank matrix completion is a problem of immense practical importance.
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