Improving neural networks by preventing co-adaptation of feature detectors
作者： Ilya Sutskever , Geoffrey E. Hinton , Alex Krizhevsky , Ruslan R. Salakhutdinov , Nitish Srivastava
DOI:
关键词: Computer science 、 Cognitive neuroscience of visual object recognition 、 Context (language use) 、 Dropout (neural networks) 、 Overfitting 、 Artificial neural network 、 Feature (computer vision) 、 Feedforward neural network 、 Benchmark (computing) 、 Training set 、 Machine learning 、 Artificial intelligence
摘要: When a large feedforward neural network is trained on a small training set, it typically performs poorly on held-out test data. This "overfitting" is greatly reduced by randomly omitting half …
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tu-darmstadt.de 参考文章(18)
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