Gradient descent is an optimization algorithm that follows the negative gradient of an objective function in order to locate the minimum of the function. A limitation of gradient descent is that it can get stuck in flat areas or bounce around if the objective function returns noisy gradients. Momentum is an approach that accelerates the […]
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