The duality structure gradient descent algorithm: analysis and applications to neural networks

1 Aug 2017 Thomas Flynn

The training of deep neural networks is typically carried out using some form of gradient descent, often with great success. However, existing non-asymptotic analyses of first-order optimization algorithms typically employ a gradient smoothness assumption that is too strong to be applicable in the case of deep neural networks... (read more)

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