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A Closer Look at Deep Policy Gradients
Andrew Ilyas, Logan Engstrom, Shibani Santurkar +4
We study how the behavior of deep policy gradient algorithms reflects the conceptual framework motivating their development. To this end, we propose a fine-grained analysis of stat…
Spectral Signatures in Backdoor Attacks
Brandon Tran, Jerry Li, Aleksander Madry
A recent line of work has uncovered a new form of data poisoning: so-called \emph{backdoor} attacks. These attacks are particularly dangerous because they do not affect a network's…
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability
Kai Y. Xiao, Vincent Tjeng, Nur Muhammad Shafiullah +1
We explore the concept of co-design in the context of neural network verification. Specifically, we aim to train deep neural networks that not only are robust to adversarial pertur…
Adversarially Robust Generalization Requires More Data
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras +2
Machine learning models are often susceptible to adversarial perturbations of their inputs. Even small perturbations can cause state-of-the-art classifiers with high "standard" acc…