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Aug 30, 2021 · This paper proposes a method for finding marginal adversarial samples based on reinforcement learning, and combines it with the latest fast ...
This paper proposes a method for finding marginal adversarial samples based on reinforcement learning, and combines it with the latest fast adversarial training ...
Aug 30, 2021 · Abstract. Adversarial training has become the primary method to defend against adversarial samples. However, it is hard to practically apply ...
A method for finding marginal adversarial samples based on reinforcement learning, and combines it with the latest fast adversarial training technology, ...
Aug 4, 2023 · Adversarial training has been shown to be the most popular and effective technique to protect models from imperceptible adversarial samples.
To keep the training stable while improving robustness, we propose a simple but effective method, namely, Adaptive Adversarial Perturbation (A2P), which can ...
This paper proposes a method for finding marginal adversarial samples based on reinforcement learning, and combines it with the latest fast adversarial training ...
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This paper proposes a method for finding marginal adversarial samples based on reinforcement learning, and combines it with the latest fast adversarial training ...
May 20, 2024 · The key idea is to train the RL agent to learn an adaptive perturbation policy that can generate adversarial perturbations to its own actions, ...
Our method can be integrated with almost all existing gradient-based attack methods to further improve their attack success rates. Extensive experiments on the ...
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