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, Pengcheng Xie
· 0 citations