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Easy Batch Normalization

2022-07-18 · Arip Asadulaev, Alexander Panfilov, Andrey Filchenkov

It was shown that adversarial examples improve object recognition. But what about their opposite side, easy examples? Easy examples are samples that the machine learning model classifies correctly with high confidence. In our paper, we are making the first step toward exploring the potential benefits of using easy examples in the training procedure of neural networks. We propose to use an auxiliary batch normalization for easy examples for the standard and robust accuracy improvement.

📄 PDF Abstract BibTeX arXiv:2207.08940

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Object Recognition

Methods 이 논문이 사용한 방법론

Batch Normalization 설명 없음
Auxiliary Batch Normalization Auxiliary Batch Normalization is a type of regularization used in adversarial training schemes. The idea is that adversarial examples should have a separate [batch…

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