[2111.12229] Subspace Adversarial Training - arXiv.org
2021年11月24日 · To control the growth of the gradient, we propose a new AT method, Subspace Adversarial Training (Sub-AT), which constrains AT in a carefully extracted subspace. It successfully resolves both kinds of overfitting and significantly boosts the robustness.
【论文阅读】2022-CVPR-Subspace Adversarial Training - 知乎
Subspace AT = DLDR + single-step AT，其中DLDR是 提出的training in subspace方法，整个过程如下： Evaluation 提出的Sub-AT能很好地将参数的梯度控制在tiny space里，不仅能防止了catastrophic overfitting，甚至还能减少robustness overfitting提高adversarial acc。
Subspace Adversarial Training - CSDN博客
2022年8月17日 · 提出子空间对抗训练 (Sub-AT)方法，通过限制AT在低维子空间内进行，有效控制梯度增长，防止过拟合，提高模型的鲁棒性。 Sub-AT不仅解决了过拟合，还降低了对学习率的敏感性，允许更大的步长和半径，实现了与多步AT相当的鲁棒性，且计算效率高。 单步 对抗训练 AT存在一个灾难性过拟合问题，在训练过程中，针对PGD攻击的文件准确性突然下降到0%。 本文揭示了每个样本的快速增长梯度与过拟合之间的密切联系，这也可以应用于理解多步骤AT中 …
nblt/Sub-AT: [CVPR 2022 oral] Subspace Adversarial Training - GitHub
To control the growth of the gradient, we propose a new AT method, Subspace Adversarial Training (Sub-AT), which constrains AT in a carefully extracted subspace. It successfully resolves both kinds of overfitting and significantly boosts the robustness.
To control the growth of the gradient, we propose a new AT method, Subspace Adversarial Training (Sub-AT), which constrains AT in a carefully extracted sub-space. It successfully resolves both kinds of overfitting and significantly boosts the robustness.
Subspace Adversarial Training | IEEE Conference Publication
2022年6月24日 · To control the growth of the gradient, we propose a new AT method, Subspace Adversarial Training (Sub-AT), which constrains AT in a carefully extracted subspace. It successfully resolves both kinds of overfitting and significantly boosts the robustness.
[2111.12229] Subspace Adversarial Training - ar5iv
The computational overhead of Sub-AT consists of two parts: DLDR and subspace training. The DLDR part contains two steps: sampling and decomposition. The time consumption on the decomposition is negligible compared to the sampling as it only involves a spectral decomposition of a t × t 𝑡 𝑡 t\times t matrix and two matrix productions. The ...
To control the growth of the gradient during the training, we propose a new AT method, subspace adversarial training (Sub-AT), which constrains the AT in a carefully extracted subspace. It successfully resolves both two kinds of overfitting and hence significantly boosts the robustness.
[PDF] Subspace Adversarial Training - Semantic Scholar
This paper proposes a new AT method, Subspace Adversarial Training (Sub-AT), which constrains AT in a carefully extracted subspace and successfully resolves both kinds of overfitting and significantly boosts the robustness.
Subspace Adversarial Training - Papers With Code
To control the growth of the gradient, we propose a new AT method, Subspace Adversarial Training (Sub-AT), which constrains AT in a carefully extracted subspace. It successfully resolves both kinds of overfitting and significantly boosts the robustness.
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