Provable Robustness of Adversarial Training for Learning Halfspaces with
Noise

Provable Robustness of Adversarial Training for Learning Halfspaces with Noise

19 April 2021

Quanquan Gu

Papers citing "Provable Robustness of Adversarial Training for Learning Halfspaces with Noise"

16 / 16 papers shown

Title
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 255 348 0 15 Dec 2021
The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise Ilias Diakonikolas D. Kane Pasin Manurangsi 62 20 0 30 Jul 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 62 424 0 16 Jul 2020
Non-Convex SGD Learns Halfspaces with Adversarial Label Noise Ilias Diakonikolas Vasilis Kontonis Christos Tzamos Nikos Zarifis 33 28 0 11 Jun 2020
Efficiently Learning Adversarially Robust Halfspaces with Noise Omar Montasser Surbhi Goel Ilias Diakonikolas Nathan Srebro 47 32 0 15 May 2020
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy Aditi Raghunathan Sang Michael Xie Fanny Yang John C. Duchi Percy Liang AAML 82 228 0 25 Feb 2020
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality Yi Zhang Orestis Plevrakis S. Du Xingguo Li Zhao Song Sanjeev Arora 103 51 0 16 Feb 2020
Learning Halfspaces with Massart Noise Under Structured Distributions Ilias Diakonikolas Vasilis Kontonis Christos Tzamos Nikos Zarifis 44 61 0 13 Feb 2020
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 87 1,836 0 06 May 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 130 2,028 0 08 Feb 2019
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 93 1,776 0 30 May 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 92 1,407 0 08 Dec 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 263 12,029 0 19 Jun 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 461 3,138 0 04 Nov 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 220 8,533 0 16 Aug 2016
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 233 14,893 1 21 Dec 2013