1 citations · 3 across the 6 of their papers we have counts for
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cs.CV2023★ 1 cited
Defenses in Adversarial Machine Learning: A Survey
Baoyuan Wu, Shaokui Wei, Mingli Zhu +7
Adversarial phenomenon has been widely observed in machine learning (ML) systems, especially in those using deep neural networks, describing that ML systems may produce inconsisten…
cs.CR2023★ 1 cited
Activation Gradient based Poisoned Sample Detection Against Backdoor Attacks
Danni Yuan, Shaokui Wei, Mingda Zhang +2
This work studies the task of poisoned sample detection for defending against data poisoning based backdoor attacks. Its core challenge is finding a generalizable and discriminativ…
cs.LG2023
Attacks in Adversarial Machine Learning: A Systematic Survey from the Life-cycle Perspective
Baoyuan Wu, Zihao Zhu, Li Liu +3
Adversarial machine learning (AML) studies the adversarial phenomenon of machine learning, which may make inconsistent or unexpected predictions with humans. Some paradigms have be…