Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adaptive perturbation adversarial training: based on reinforcement
  learning   Adversarial training has become the primary method to defend against
adversarial samples. However, it is hard to practically apply due to many
shortcomings. One of the shortcomings of adversarial training is that it will
reduce the recognition accuracy of normal samples. Adaptive perturbation
adversarial training is proposed to alleviate this problem. It uses marginal
adversarial samples that are close to the decision boundary but does not cross
the decision boundary for adversarial training, which improves the accuracy of
model recognition while maintaining the robustness of the model. However,
searching for marginal adversarial samples brings additional computational
costs. This paper proposes a method for finding marginal adversarial samples
based on reinforcement learning, and combines it with the latest fast
adversarial training technology, which effectively speeds up training process
and reduces training costs.

21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
6
The categories of this paper are: astro-ph
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics