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Results tagged with gradient-descent
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user 14586
Gradient Descent is an algorithm for finding the minimum of a function. It iteratively calculates partial derivatives (gradients) of the function and descends in steps proportional to those partial derivatives. One major application of Gradient Descent is fitting a parameterized model to a set of data: the function to be minimized is an error function for the model.
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Should weights on earlier layers change less than weights on later layers in a neural network
I'm trying to debug why my neural network isn't working. One of the things I've observed is that the weights between the input layer and the first hidden layer hardly change at all, whereas weights la …
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