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2020 – today
- 2023
[c9]Amin Ghiasi, Ali Shafahi, Reza Ardekani:
Improving Robustness with Adaptive Weight Decay. NeurIPS 2023- 2022
- [c8]Avi Schwarzschild, Arjun Gupta, Amin Ghiasi, Micah Goldblum, Tom Goldstein:
The Uncanny Similarity of Recurrence and Depth. ICLR 2022 - [c7]Amin Ghiasi, Hamid Kazemi, Steven Reich, Chen Zhu, Micah Goldblum, Tom Goldstein:
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations. ICML 2022: 7484-7512 - [i10]Amin Ghiasi, Hamid Kazemi, Steven Reich, Chen Zhu, Micah Goldblum, Tom Goldstein:
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations. CoRR abs/2201.12961 (2022) - [i9]Amin Ghiasi, Ali Shafahi, Reza Ardekani:
Adaptive Weight Decay: On The Fly Weight Decay Tuning for Improving Robustness. CoRR abs/2210.00094 (2022) - [i8]Amin Ghiasi, Hamid Kazemi, Eitan Borgnia, Steven Reich, Manli Shu, Micah Goldblum, Andrew Gordon Wilson, Tom Goldstein:
What do Vision Transformers Learn? A Visual Exploration. CoRR abs/2212.06727 (2022) - 2021
- [c6]Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta:
Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. ICASSP 2021: 3855-3859 - [c5]Amin Ghiasi, Masoud Seddighin
:
Approximate Competitive Equilibrium with Generic Budget. SAGT 2021: 236-250 - [i7]Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein:
DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations. CoRR abs/2103.02079 (2021) - 2020
- [c4]Amin Ghiasi, Ali Shafahi, Tom Goldstein:
Breaking Certified Defenses: Semantic Adversarial Examples with Spoofed robustness Certificates. ICLR 2020 - [c3]Ali Shafahi, Parsa Saadatpanah, Chen Zhu, Amin Ghiasi, Christoph Studer, David W. Jacobs, Tom Goldstein:
Adversarially robust transfer learning. ICLR 2020 - [i6]Amin Ghiasi, Ali Shafahi, Tom Goldstein:
Breaking certified defenses: Semantic adversarial examples with spoofed robustness certificates. CoRR abs/2003.08937 (2020) - [i5]Chen Zhu, Zheng Xu, Ali Shafahi, Manli Shu, Amin Ghiasi, Tom Goldstein:
Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer. CoRR abs/2010.07334 (2020) - [i4]Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta:
Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. CoRR abs/2011.09527 (2020)
2010 – 2019
- 2019
- [c2]Ali Shafahi, Amin Ghiasi, Mahyar Najibi, Furong Huang, John P. Dickerson, Tom Goldstein:
Batch-wise Logit-Similarity: Generalizing Logit-Squeezing and Label-Smoothing. BMVC 2019: 72 - [c1]Ali Shafahi, Mahyar Najibi, Amin Ghiasi, Zheng Xu, John P. Dickerson, Christoph Studer, Larry S. Davis, Gavin Taylor, Tom Goldstein:
Adversarial training for free! NeurIPS 2019: 3353-3364 - [i3]Ali Shafahi, Mahyar Najibi, Amin Ghiasi, Zheng Xu, John P. Dickerson, Christoph Studer, Larry S. Davis, Gavin Taylor, Tom Goldstein:
Adversarial Training for Free! CoRR abs/1904.12843 (2019) - [i2]Ali Shafahi, Parsa Saadatpanah, Chen Zhu, Amin Ghiasi, Christoph Studer, David W. Jacobs, Tom Goldstein:
Adversarially robust transfer learning. CoRR abs/1905.08232 (2019) - [i1]Ali Shafahi, Amin Ghiasi, Furong Huang, Tom Goldstein:
Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training? CoRR abs/1910.11585 (2019)
Coauthor Index
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