(c. early 2013)
Iteratively put more detail when training:
Represent a low approximation, and train.
Given the best solution there, now approximate the function with a bit more detail, and repeat, starting at the point of the best solution given in the last iteration.
Iteratively put more detail when training:
Represent a low approximation, and train.
Given the best solution there, now approximate the function with a bit more detail, and repeat, starting at the point of the best solution given in the last iteration.
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