Towards automatically-tuned deep neural networks
Abstract: Recent advances in AutoML have led to automated tools that can compete with machine learning experts on supervised learning tasks. In this work, we present two versions of Auto-Net, which provide automatically-tuned deep neural networks without any human intervention. The first version, Auto-Net 1.0, builds upon ideas from the competition-winning system Auto-sklearn by using the Bayesian Optimization method SMAC and uses Lasagne as the underlying deep learning (DL) library. The more recent Auto-Net 2.0 builds upon a recent combination of Bayesian Optimization and HyperBand, called BOHB, and uses PyTorch as DL library. To the best of our knowledge, Auto-Net 1.0 was the first automatically-tuned neural network to win competition datasets against human experts (as part of the first AutoML challenge). Further empirical results show that ensembling Auto-Net 1.0 with Auto-sklearn can perform better than either approach alone, and that Auto-Net 2.0 can perform better yet
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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Automated Machine Learning. - Cham : Hutter, Frank; Kotthoff, Lars; Vanschoren, Joaquin [Hrsg.], 2019. - 135-149, ISBN: 978-3-030-05318-5
- Event
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Veröffentlichung
- (where)
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Freiburg
- (who)
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Universität
- (when)
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2024
- Creator
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Mendoza, Hector
Klein, Aaron
Feurer, Matthias
Springenberg, Jost Tobias
Urban, Matthias
Burkart, Michael
Dippel, Maximilian
Lindauer, Marius
Hutter, Frank
- Contributor
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Maschinelles Lernen und Natürlichsprachliche Systeme, Professur Frank Hutter
- DOI
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10.1007/978-3-030-05318-5_7
- URN
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urn:nbn:de:bsz:25-freidok-1542403
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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25.03.2025, 1:50 PM CET
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Mendoza, Hector
- Klein, Aaron
- Feurer, Matthias
- Springenberg, Jost Tobias
- Urban, Matthias
- Burkart, Michael
- Dippel, Maximilian
- Lindauer, Marius
- Hutter, Frank
- Maschinelles Lernen und Natürlichsprachliche Systeme, Professur Frank Hutter
- Universität
Time of origin
- 2024
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