375 citations · 375 across the 2 of their papers we have counts for
2 papers
cs.LG2024
DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation
Yunjuan Wang, Hussein Hazimeh, Natalia Ponomareva +3
Distribution shifts and adversarial examples are two major challenges for deploying machine learning models. While these challenges have been studied individually, their combinatio…
cs.CV2016★ 375 cited
Adversarial Machine Learning at Scale
Alexey Kurakin, Ian Goodfellow, Samy Bengio
Adversarial examples are malicious inputs designed to fool machine learning models. They often transfer from one model to another, allowing attackers to mount black box attacks wit…