NAS-HPO-Bench-II-Plus: A Surrogate Benchmark Dataset Toward Practical Scenarios in Joint Neural Architecture Search and Hyperparameter Optimization

Automated machine learning reduces the manual effort required to design deep learning models. Its two major subfields, neural architecture search and hyperparameter optimization, optimize model architectures and training hyperparameters, respectively. In practice, they are often applied sequentially...

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Bibliografiske detaljer

Principais autores:	Yoichi Hirose, Kento Uchida, Shinichi Shirakawa
Format:	Artigo
Sprog:	Inglês
Udgivet:	IEEE 2026-01-01
Serier:	IEEE Access
Fag:	Automated machine learning hyperparameter optimization neural architecture search image recognition joint neural architecture search and hyperparameter optimization surrogate benchmark datasets
Online adgang:	https://ieeexplore.ieee.org/document/11606383/
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