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Results tagged with gradient-descent
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user 12383
For questions surrounding gradient descent, a method for finding the optimum state of a parameterized function based on another function often called the loss or error function. It iteratively descends the loss surface to the minimum loss by adjusting parameters based on the product of the partial derivatives comprising the gradient and a learning rate.
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What are some concrete steps to deal with the vanishing gradient problem?
There is not single answer to the vanishing gradient problem. However, there a few things that can help.
As mentioned in the comments, use of Rectified Linear Units (ReLU) as your activation function …
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