Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning

In this study, we propose the leveraging of interpretability for tasks beyond purely the purpose of explainability. In particular, this study puts forward a novel strategy for leveraging gradient-based interpretability in the realm of adversarial examples, where we use insights gained to aid adversa...

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Bibliographische Detailangaben

Hauptverfasser:	Kumar, Devinder, Ben-Daya, Ibrahim, Vats, Kanav, Feng, Jeffery, and, Graham Taylor, Wong, Alexander
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Cryptography and Security Computer Science - Learning Statistics - Machine Learning
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