Why and When Neural Networks Improve Local Approximation in Optimization
It is shown that the contradiction in experience with neural surrogates in derivative-free optimisation dissolves once three factors are stated, and that these, rather than the fit accuracy a training curve reports, are what delimit when a learned local model pays.
Cheng Bian, Peng-Cheng Xie
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