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cs.LG2022
A Novel Plug-and-Play Approach for Adversarially Robust Generalization
Deepak Maurya, Adarsh Barik, Jean Honorio
In this work, we propose a robust framework that employs adversarially robust training to safeguard the ML models against perturbed testing data. Our contributions can be seen from…
cs.LG2022
Sparse Mixed Linear Regression with Guarantees: Taming an Intractable Problem with Invex Relaxation
Adarsh Barik, Jean Honorio
In this paper, we study the problem of sparse mixed linear regression on an unlabeled dataset that is generated from linear measurements from two different regression parameter vec…