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Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses


Dec 30, 2020
Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein


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Data Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses


Dec 18, 2020
Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein


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BREEDS: Benchmarks for Subpopulation Shift


Aug 11, 2020
Shibani Santurkar, Dimitris Tsipras, Aleksander Madry


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Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO


May 25, 2020
Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

* ICLR 2020 version. arXiv admin note: text overlap with arXiv:1811.02553 

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From ImageNet to Image Classification: Contextualizing Progress on Benchmarks


May 22, 2020
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry


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Identifying Statistical Bias in Dataset Replication


May 19, 2020
Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry


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Label-Consistent Backdoor Attacks


Dec 06, 2019
Alexander Turner, Dimitris Tsipras, Aleksander Madry


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Computer Vision with a Single (Robust) Classifier


Jun 06, 2019
Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Andrew Ilyas, Logan Engstrom, Aleksander Madry


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Learning Perceptually-Aligned Representations via Adversarial Robustness


Jun 03, 2019
Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Aleksander Madry


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Adversarial Examples Are Not Bugs, They Are Features


May 07, 2019
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry


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On Evaluating Adversarial Robustness


Feb 20, 2019
Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian Goodfellow, Aleksander Madry, Alexey Kurakin

* Living document; source available at https://github.com/evaluating-adversarial-robustness/adv-eval-paper/ 

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Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms?


Dec 02, 2018
Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry


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How Does Batch Normalization Help Optimization?


Oct 27, 2018
Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry

* To appear in NIPS'18 

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Robustness May Be at Odds with Accuracy


Oct 11, 2018
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry


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Adversarially Robust Generalization Requires More Data


May 02, 2018
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Mądry

* Small changes for biblatex compatibility 

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A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations


Feb 13, 2018
Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry

* Preliminary version appeared in the NIPS 2017 Workshop on Machine Learning and Computer Security 

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Towards Deep Learning Models Resistant to Adversarial Attacks


Nov 09, 2017
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu


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