Multi-Label Adversarial Perturbations 文章目录 Multi-Label Adversarial Perturbations ICDM2018 1.介绍 1.1多标签对抗样本广泛存在于现实生活中。 1.2生成多标签对抗样本的挑战。 1.3针对多标签攻击本文设计了2种框架4种方法 2.符号 2.1有目标攻击定义 3.多标签目标攻击 3.1 Classification-targeted Framework 3.1.1 ML...
[论文总结] Multi-label Adversarial Perturbations 说在前面 ICDM 2018,原文链接:https://arxiv.org/abs/1901.00546 暂无开源代码。 本文作于2021年09月26日。 1. 解决的问题 虽然现有工作侧重于在多类分类问题中生成对抗扰动,但许多实际应用都属于多标签设置,其中一个实例可能与多个标签相关联。为了分析多标签学习...
Adversarial examples which mislead deep neural networks by adding well-crafted perturbations have become a major threat to classification models. Gradient-based white-box attack algorithms have been widely used to generate adversarial examples. However, most of them are designed for multi-class models,...