Understanding deep learning requires rethinking generalization
Understanding deep learning requires rethinking generalization 在部分/全部随机标签的CIFAR-10数据集，以及加入了高斯噪音的图片上的表现。如果在随机生成的分类标签上，模型表现的也很好，这对于模型的泛化能力意味着什么? 先让我们看看文中给出的数据，A图指出，不管怎样在模型中怎样引入随机性，在图像中加入随机噪音，对像素进行随机洗牌
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相关文章
- 1. 『 论文阅读』Understanding deep learning requires rethinking generalization
- 2. 论文笔记 understanding deep learning requires rethinking generalization
- 3. What’s New in Deep Learning Research: Understanding Meta-Learning
- 4. (转) Awesome - Most Cited Deep Learning Papers
- 5. Applied Deep Learning Resources
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