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Why and When Neural Networks Improve Local Approximation in Optimization

This story is from 2026-08-27. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2608.24963v1 Announce Type: new Abstract: Published experience with neural surrogates in derivative-free optimisation is contradictory: the same family of models that cuts the evaluation count of one solver leaves another unchanged, or makes it worse. We show that the contradiction dissolves…

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  1. 2026-08-27 04:00 · arXiv cs.LG
    Why and When Neural Networks Improve Local Approximation in Optimization

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