What common optimization challenge can prevent gradient descent from reaching the desired level of accuracy specified by the UAT?
Answer
The optimization process getting stuck in a local minimum.
Even though the global minimum (perfect approximation) exists on the error surface, gradient descent might stop at a local minimum, resulting in a good but not maximally accurate approximation.
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