Learn to optimize—a brief overview

Most optimization problems of practical significance are typically solved by highly configurable parameterized algorithms. To achieve the best performance on a problem instance, a trial-and-error configuration process is required, which is very costly and even prohibitive for problems that are alrea...

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Vydané v:	National science review Ročník 11; číslo 8; s. nwae132
Hlavní autori:	Tang, Ke, Yao, Xin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	China Oxford University Press 01.08.2024
Predmet:	data-driven algorithm design machine learning optimization automated algorithm configuration
ISSN:	2095-5138, 2053-714X, 2053-714X
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