严厉谴责
发表于 2025-3-28 16:44:15
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inchoate
发表于 2025-3-28 22:21:00
,Industry and Trade, 1800–1938,ximated certified robustness (UniCR) framework, which can approximate the robustness certification of . input on . classifier against . . perturbations with noise generated by . continuous probability distribution. Compared with the state-of-the-art certified defenses, UniCR provides many significan
光明正大
发表于 2025-3-28 23:17:20
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pineal-gland
发表于 2025-3-29 04:25:27
The Sixteenth-Century Growth of the Marketdomains. Most of existing methods improve model robustness from weight optimization, such as adversarial training. However, the architecture of DNNs is also a key factor to robustness, which is often neglected or underestimated. We propose Robust Network Architecture Search (RNAS) to obtain a robust
Diuretic
发表于 2025-3-29 10:19:02
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乐意
发表于 2025-3-29 13:46:30
Disputes and Levels of Litigationdiction label. Great efforts have been made recently to decrease the number of queries; however, existing decision-based attacks still require thousands of queries in order to generate good quality adversarial examples. In this work, we find that a benign sample, the current and the next adversarial
Stable-Angina
发表于 2025-3-29 17:55:13
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令人作呕
发表于 2025-3-29 22:56:50
Disputes and Levels of Litigational hard-label setting, we observe that existing methods suffer from catastrophic performance degradation. We argue this is due to the lack of rich information in the probability prediction and the overfitting caused by hard labels. To this end, we propose a novel hard-label model stealing method ter
和谐
发表于 2025-3-30 00:12:14
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GUEER
发表于 2025-3-30 04:22:53
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