Dropout: A Simple Way to Prevent Neural Networks from Overfitting
GPTKB entity
Statements (20)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:academic_journal
|
| gptkbp:arXivID |
1207.0580
|
| gptkbp:author |
gptkb:Nitish_Srivastava
gptkb:Alex_Krizhevsky gptkb:Geoffrey_Hinton gptkb:Ilya_Sutskever gptkb:Ruslan_Salakhutdinov |
| gptkbp:citation |
over 50000
|
| gptkbp:field |
gptkb:machine_learning
deep learning |
| gptkbp:hasMethod |
dropout
|
| gptkbp:influenced |
regularization techniques in neural networks
|
| gptkbp:language |
English
|
| gptkbp:publicationYear |
2014
|
| gptkbp:publishedIn |
gptkb:Journal_of_Machine_Learning_Research
|
| gptkbp:url |
https://arxiv.org/abs/1207.0580
https://jmlr.org/papers/v15/srivastava14a.html |
| gptkbp:bfsParent |
gptkb:NeurIPS_2014
|
| gptkbp:bfsLayer |
7
|
| http://www.w3.org/2000/01/rdf-schema#label |
Dropout: A Simple Way to Prevent Neural Networks from Overfitting
|