1 code implementation • 2 Nov 2023 • Bhagyashree Puranik, Ahmad Beirami, Yao Qin, Upamanyu Madhow
State-of-the-art techniques for enhancing robustness of deep networks mostly rely on empirical risk minimization with suitable data augmentation.
no code implementations • 4 Dec 2021 • Bhagyashree Puranik, Upamanyu Madhow, Ramtin Pedarsani
We derive the worst-case attack for the GLRT defense, and show that its asymptotic performance (as the dimension of the data increases) approaches that of the minimax defense.
no code implementations • 16 Nov 2020 • Bhagyashree Puranik, Upamanyu Madhow, Ramtin Pedarsani
We evaluate the GLRT approach for the special case of binary hypothesis testing in white Gaussian noise under $\ell_{\infty}$ norm-bounded adversarial perturbations, a setting for which a minimax strategy optimizing for the worst-case attack is known.