(10) [JMLR14] Dropout: A Simple Way to Prevent Neural Networks from Overfitting
计划完成深度学习入门的126篇论文第十篇，多伦多大学的Geoffrey Hinton·和Alex Krizhevsky使用一种新的regularization方法Dropout。 ABSTRACT&INTRODUCTION 摘要 具有大量参数的深度神经网络是非常强大的机器学习系统。然而，在这样的网络中，过拟合是一个严重的问题。大型网络的使用也很缓慢，通过在测试时结合许多不同的大型神经网络的预测，很
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相关文章
- 1. (10) [JMLR14] Dropout: A Simple Way to Prevent Neural Networks from Overfitting
- 2. Dropout:A Simple Way to Prevent Neural Networks from Overfitting
- 3. 【论文精读】Dropout: A Simple Way to Prevent Neural Networks from Overfitting
- 4. 译：《Dropout: A Simple Way to Prevent Neural Networks from Overfitting》
- 5. Dropout: A Simple Way to Prevent Neural Networks from Over tting 论文阅读
- 6. 论文笔记2——Dropout：A simple way to prevent neural networks from overfitting
- 7. A Beginner's Guide To Understanding Convolutional Neural Networks - Part 2
- 8. 【转】A Beginner's Guide To Understanding Convolutional Neural Networks
- 9. A Beginner's Guide To Understanding Convolutional Neural Networks(转)
- 10. A Beginner's Guide To Understanding Convolutional Neural Networks - Part 1