Gradient descent with momentum --- to accelerate or to super-accelerate?

17 Jan 2020Goran NakerstJohn BrennanMasudul Haque

We consider gradient descent with `momentum', a widely used method for loss function minimization in machine learning. This method is often used with `Nesterov acceleration', meaning that the gradient is evaluated not at the current position in parameter space, but at the estimated position after one step... (read more)

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