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We present a unifying framework for adapting the update direction ingradient-based iterative optimization methods. As natural special cases were-derive classical momentum and Nesterov's accelerated gradient method,lending a new intuitive interpretation to the latter algorithm. We show that anew algorithm, which we term Regularised Gradient Descent, can converge morequickly than either Nesterov's algorithm or the classical momentum algorithm.

Nesterov's Accelerated Gradient and Momentum as approximations to Regularised Update Descent