1 citations · 1 across the 3 of their papers we have counts for
3 papers
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…
Leveraging Importance Weights in Subset Selection
Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar +3
We present a subset selection algorithm designed to work with arbitrary model families in a practical batch setting. In such a setting, an algorithm can sample examples one at a ti…
Adversarial Robustness is at Odds with Lazy Training
Yunjuan Wang, Enayat Ullah, Poorya Mianjy +1
Recent works show that adversarial examples exist for random neural networks [Daniely and Schacham, 2020] and that these examples can be found using a single step of gradient ascen…