Model-Reuse Attacks on Deep Learning Systems
Model-Reuse Attacks on Deep Learning Systems阅读笔记 文献背景及解决问题 核心方法 论文优点 总结与想法 文献背景及解决问题 现如今许多机器学习(ML)系统都是通过重用一组通常经过预先训练的原始模型来构建的(例如，特征提取)，越来越多的原始模型的使用意味着简化和加速了ML系统的开发周期，但由于大多数此类模型都是由不可信的来源提供和维护的，缺乏标准化或监管
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相关文章
- 1. Model-Reuse Attacks on Deep Learning Systems
- 2. A Survey of Recommender Systems Based on Deep Learning （1）
- 3. Paper Reading:Wide & Deep Learning for Recommender Systems
- 4. Wide & Deep Learning for Recommender Systems
- 5. Collaborative Deep Learning for Recommender Systems
- 6. Wide &Deep Learning for Recommender Systems
- 7. [论文解读]Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
- 8. [转载][paper]Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
- 9. PGD:Towards Deep Learning Models Resistant to Adversarial Attacks
- 10. 「Deep Learning」Note on RetinaNet