BAG OF TRICKS FOR ADVERSARIAL TRAINING
对抗训练是最有效的用于提升模型鲁棒性的策略之一。 但是在AT上的许多改进不如简单地提前停止训练过程有效。 基础参数设置的不同对模型的鲁棒性有很大的影响。 本文对基础训练技巧和超参数的设置在对抗性训练模型的影响提供了综合性的评估。 十篇文章中的实现细节： 超参数设置非常不一致，不能直接对这些方法排序。 PGD-AT 在 CIFAR-10 上作为例子 默认设置： PGD-AT框架 batc
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相关文章
- 1. Bag of Tricks for Convolutional Neural Networks
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- 3. Bag of Tricks for Image Classification with Convolutional Neural Networks
- 4. Bag of Freebies for Training Object Detection Neural Networks
- 5. (36)[EACL] Bag of Tricks for Efficient Text Classification
- 6. DANN：Domain-Adversarial Training of Neural Networks
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