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Eric Wong
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Provable defenses against adversarial examples via the convex outer adversarial polytope
E Wong, JZ Kolter
arXiv preprint arXiv:1711.00851, 2017
15842017
Provable defenses against adversarial examples via the convex outer adversarial polytope
E Wong, J Zico Kolter
arXiv preprint arXiv:1711.00851, 2017
15842017
Fast is better than free: Revisiting adversarial training
E Wong, L Rice, JZ Kolter
arXiv preprint arXiv:2001.03994, 2020
11432020
Overfitting in adversarially robust deep learning
L Rice, E Wong, Z Kolter
International Conference on Machine Learning, 8093-8104, 2020
7952020
Scaling provable adversarial defenses
E Wong, F Schmidt, JH Metzen, JZ Kolter
Advances in Neural Information Processing Systems, 8400-8409, 2018
4492018
Wasserstein adversarial examples via projected sinkhorn iterations
E Wong, F Schmidt, Z Kolter
International Conference on Machine Learning, 6808-6817, 2019
2432019
Adversarial robustness against the union of multiple perturbation models
P Maini, E Wong, Z Kolter
International Conference on Machine Learning, 6640-6650, 2020
1592020
Faithful Chain-of-Thought Reasoning
Q Lyu, S Havaldar, A Stein, L Zhang, D Rao, E Wong, M Apidianaki, ...
arXiv preprint arXiv:2301.13379, 2023
1002023
Jailbreaking black box large language models in twenty queries
P Chao, A Robey, E Dobriban, H Hassani, GJ Pappas, E Wong
arXiv preprint arXiv:2310.08419, 2023
972023
Leveraging sparse linear layers for debuggable deep networks
E Wong, S Santurkar, A Madry
International Conference on Machine Learning, 11205-11216, 2021
782021
Learning perturbation sets for robust machine learning
E Wong, JZ Kolter
arXiv preprint arXiv:2007.08450, 2020
682020
Smoothllm: Defending large language models against jailbreaking attacks
A Robey, E Wong, H Hassani, GJ Pappas
arXiv preprint arXiv:2310.03684, 2023
552023
Certified patch robustness via smoothed vision transformers
H Salman, S Jain, E Wong, A Madry
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
542022
Adversarial Prompting for Black Box Foundation Models
N Maus, P Chao, E Wong, J Gardner
arXiv preprint arXiv:2302.04237, 2023
402023
A semismooth Newton method for fast, generic convex programming
A Ali, E Wong, JZ Kolter
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
272017
A Data-Based Perspective on Transfer Learning
S Jain, H Salman, A Khaddaj, E Wong, SM Park, A Mądry
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
262023
In-context Example Selection with Influences
T Nguyen, E Wong
arXiv preprint arXiv:2302.11042, 2023
222023
Missingness Bias in Model Debugging
S Jain, H Salman, E Wong, P Zhang, V Vineet, S Vemprala, A Madry
International Conference on Learning Representations, 2021
222021
When does Bias Transfer in Transfer Learning?
H Salman, S Jain, A Ilyas, L Engstrom, E Wong, A Madry
arXiv preprint arXiv:2207.02842, 2022
212022
How many random restarts are enough?
T Dick, E Wong, C Dann
Google Scholar, 2014
172014
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Articles 1–20