3 papers
cs.CV2018
On The Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces
Chia-Yi Hsu, Pei-Hsuan Lu, Pin-Yu Chen +1
Recent studies have found that deep learning systems are vulnerable to adversarial examples; e.g., visually unrecognizable adversarial images can easily be crafted to result in mis…
cs.CV2018
On the Limitation of MagNet Defense against -based Adversarial Examples
Pei-Hsuan Lu, Pin-Yu Chen, Kang-Cheng Chen +1
In recent years, defending adversarial perturbations to natural examples in order to build robust machine learning models trained by deep neural networks (DNNs) has become an emerg…
cs.LG2018
On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples
Pei-Hsuan Lu, Pin-Yu Chen, Chia-Mu Yu
Understanding and characterizing the subspaces of adversarial examples aid in studying the robustness of deep neural networks (DNNs) to adversarial perturbations. Very recently, Ma…