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Results tagged with gradient-descent
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user 179490
Gradient descent is a first-order iterative optimization algorithm. To find a local minimum of a function using gradient descent, one takes steps proportional to the negative of the gradient (or of the approximate gradient) of the function at the current point. For stochastic gradient descent there is also the [sgd] tag.
9
votes
Cost function turning into nan after a certain number of iterations
Possible reasons:
Gradient blow up
Your input contains nan (or unexpected values)
Loss function not implemented properly
Numerical instability in the Deep learning framework
You can check whether …
- 466