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Towards Transferable Adversarial Attacks on Vision Transformers


Sep 09, 2021
Zhipeng Wei, Jingjing Chen, Micah Goldblum, Zuxuan Wu, Tom Goldstein, Yu-Gang Jiang


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Robustness Disparities in Commercial Face Detection


Aug 27, 2021
Samuel Dooley, Tom Goldstein, John P. Dickerson


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Datasets for Studying Generalization from Easy to Hard Examples


Aug 13, 2021
Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Arpit Bansal, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein


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Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability


Aug 03, 2021
Roman Levin, Manli Shu, Eitan Borgnia, Furong Huang, Micah Goldblum, Tom Goldstein


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Long-Short Transformer: Efficient Transformers for Language and Vision


Jul 27, 2021
Chen Zhu, Wei Ping, Chaowei Xiao, Mohammad Shoeybi, Tom Goldstein, Anima Anandkumar, Bryan Catanzaro


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Adversarial Examples Make Strong Poisons


Jun 21, 2021
Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojtek Czaja, Tom Goldstein


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MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data


Jun 17, 2021
Arpit Bansal, Micah Goldblum, Valeriia Cherepanova, Avi Schwarzschild, C. Bayan Bruss, Tom Goldstein


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Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch


Jun 16, 2021
Hossein Souri, Micah Goldblum, Liam Fowl, Rama Chellappa, Tom Goldstein


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Learning Revenue-Maximizing Auctions With Differentiable Matching


Jun 15, 2021
Michael J. Curry, Uro Lyi, Tom Goldstein, John Dickerson


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Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks


Jun 08, 2021
Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein


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SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training


Jun 02, 2021
Gowthami Somepalli, Micah Goldblum, Avi Schwarzschild, C. Bayan Bruss, Tom Goldstein


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The Intrinsic Dimension of Images and Its Impact on Learning


Apr 18, 2021
Phillip Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein

* To appear at ICLR 2021 (spotlight), 17 pages with appendix, 15 figures 

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THAT: Two Head Adversarial Training for Improving Robustness at Scale


Mar 25, 2021
Zuxuan Wu, Tom Goldstein, Larry S. Davis, Ser-Nam Lim


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Insta-RS: Instance-wise Randomized Smoothing for Improved Robustness and Accuracy


Mar 21, 2021
Chen Chen, Kezhi Kong, Peihong Yu, Juan Luque, Tom Goldstein, Furong Huang


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Thinking Deeply with Recurrence: Generalizing from Easy to Hard Sequential Reasoning Problems


Mar 17, 2021
Avi Schwarzschild, Arjun Gupta, Micah Goldblum, Tom Goldstein


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Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving


Mar 15, 2021
Shivam Akhauri, Laura Zheng, Tom Goldstein, Ming Lin

* 6 pages, 3 figures, 8 tables 

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Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release


Mar 05, 2021
Liam Fowl, Ping-yeh Chiang, Micah Goldblum, Jonas Geiping, Arpit Bansal, Wojtek Czaja, Tom Goldstein


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DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations


Mar 02, 2021
Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein

* 11 pages, 5 figures 

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What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors


Feb 26, 2021
Jonas Geiping, Liam Fowl, Gowthami Somepalli, Micah Goldblum, Michael Moeller, Tom Goldstein

* 17 pages, 14 figures 

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Improving Robustness of Learning-based Autonomous Steering Using Adversarial Images


Feb 26, 2021
Yu Shen, Laura Zheng, Manli Shu, Weizi Li, Tom Goldstein, Ming C. Lin


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Center Smoothing for Certifiably Robust Vector-Valued Functions


Feb 19, 2021
Aounon Kumar, Tom Goldstein


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GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training


Feb 16, 2021
Chen Zhu, Renkun Ni, Zheng Xu, Kezhi Kong, W. Ronny Huang, Tom Goldstein


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Technical Challenges for Training Fair Neural Networks


Feb 12, 2021
Valeriia Cherepanova, Vedant Nanda, Micah Goldblum, John P. Dickerson, Tom Goldstein


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LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition


Jan 25, 2021
Valeriia Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John Dickerson, Gavin Taylor, Tom Goldstein

* Published as a conference paper at ICLR 2021 

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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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