Randomness Regularization With Simple Consistency Training for Neural Networks
Randomness is widely introduced in neural network training to simplify model optimization or avoid the over-fitting problem. Among them, dropout and its variations in different aspects (e.g., data, model structure) are prevalent in regularizing the training of deep neural networks. Though effective...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 8 vom: 27. Aug., Seite 5763-5778
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| 1. Verfasser: |
Li, Juntao
(VerfasserIn) |
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| Weitere Verfasser: |
Liang, Xiaobo,
Wu, Lijun,
Wang, Yue,
Meng, Qi,
Qin, Tao,
Zhang, Min,
Liu, Tie-Yan |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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