Adversarial examples have emerged as a key threat for machine-learning-based systems, especially the ones that employ deep neural networks. Unlike a large body of research in this area, this Keynote article accounts for the semantic, context, and specifications of the complete system with machine learning components in resource-constrained environments. —Muhammad Shafique, Technische Universität Wien

中文翻译：

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语义对抗深度学习

对抗性示例已成为基于机器学习的系统的主要威胁，尤其是那些使用深度神经网络的系统。与该领域的大量研究不同，本主题演讲介绍了在资源受限的环境中具有机器学习组件的完整系统的语义，上下文和规范。—维也纳工业大学的穆罕默德·沙菲克（Muhammad Shafique）