This paper reports the results and post-challenge analyses of ChaLearn's AutoDL challenge series, which helped sorting out a profusion of AutoML solutions for Deep Learning (DL) that had been introduced in a variety of settings, but lacked fair comparisons. All input data modalities (time serie...
Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 43(2021), 9 vom: 23. Sept., Seite 3108-3125
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| Auteur principal: |
Liu, Zhengying
(Auteur) |
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| Autres auteurs: |
Pavao, Adrien,
Xu, Zhen,
Escalera, Sergio,
Ferreira, Fabio,
Guyon, Isabelle,
Hong, Sirui,
Hutter, Frank,
Ji, Rongrong,
Junior, Julio C S Jacques,
Li, Ge,
Lindauer, Marius,
Luo, Zhipeng,
Madadi, Meysam,
Nierhoff, Thomas,
Niu, Kangning,
Pan, Chunguang,
Stoll, Danny,
Treguer, Sebastien,
Wang, Jin,
Wang, Peng,
Wu, Chenglin,
Xiong, Youcheng,
Zela, Arber,
Zhang, Yang |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2021
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article
Research Support, Non-U.S. Gov't |
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