29 citations · 41 across the 3 of their papers we have counts for
3 papers
cs.CV2018★ 1 cited
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★ 11 cited
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★ 29 cited
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…