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...

Full description

Bibliographic Details

Published in:	National science review Vol. 11; no. 8; p. nwae132
Main Authors:	Tang, Ke, Yao, Xin
Format:	Journal Article
Language:	English
Published:	China Oxford University Press 01.08.2024
Subjects:	data-driven algorithm design machine learning optimization automated algorithm configuration
ISSN:	2095-5138, 2053-714X, 2053-714X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!