Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization

Neural architecture search (NAS) and hyperparameter optimization (HPO) make deep learning accessible to non-experts by automatically finding the architecture of the deep neural network to use and tuning the hyperparameters of the used training pipeline. While both NAS and HPO have been studied exten...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	arXiv.org 2021-05
Hauptverfasser:	Guerrero-Viu, Julia, Hauns, Sven, Izquierdo, Sergio, Miotto, Guilherme, Schrodi, Simon, Biedenkapp, Andre, Elsken, Thomas, Deng, Difan, Lindauer, Marius, Hutter, Frank
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Machine learning Multiple objective analysis Neural networks Optimization
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!