Data-driven algorithm selection and tuning in optimization and signal processing

Machine learning algorithms typically rely on optimization subroutines and are well known to provide very effective outcomes for many types of problems. Here, we flip the reliance and ask the reverse question: can machine learning algorithms lead to more effective outcomes for optimization problems?...

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Podrobná bibliografie
Vydáno v:	Annals of mathematics and artificial intelligence Ročník 89; číslo 7; s. 711 - 735
Hlavní autoři:	De Loera, Jesús A., Haddock, Jamie, Ma, Anna, Needell, Deanna
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.07.2021 Springer Springer Nature B.V
Témata:	Algorithms Artificial Intelligence Complex Systems Computer Science Data mining Data processing Data science Machine learning Mathematics Neural networks Optimization Performance enhancement Signal processing Subroutines 68T05 Neural networks Algorithm selection Automated machine learning 65K10 90C26 68T07 Compressed sensing Hyperparameter tuning
ISSN:	1012-2443, 1573-7470
On-line přístup:	Získat plný text
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