AI brief
A question on AI Stack Exchange asks for a mathematical explanation of why stochastic gradient descent can escape local minima that batch gradient descent would not.
Written by AI from AI Stack Exchange's published text.
Source
“SGD is able to jump out of local minima that would otherwise trap BGD I don't really understand the above statement.”
Interpretation or community commentary rather than straight reporting.
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