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Andrew Ilyas
Andrew Ilyas
Massachusetts Institute of Technology
Verifierad e-postadress på mit.edu - Startsida
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How Does Batch Normalization Help Optimization?
S Santurkar, D Tsipras, A Ilyas, A Madry
2358*
Adversarial examples are not bugs, they are features
A Ilyas, S Santurkar, D Tsipras, L Engstrom, B Tran, A Madry
Advances in Neural Information Processing Systems, 125-136, 2019
22402019
Synthesizing robust adversarial examples
A Athalye, L Engstrom, A Ilyas, K Kwok
arXiv preprint arXiv:1707.07397, 2017
20972017
Black-box adversarial attacks with limited queries and information
A Ilyas, L Engstrom, A Athalye, J Lin
International Conference on Machine Learning, 2137-2146, 2018
15162018
Implementation matters in deep rl: A case study on ppo and trpo
L Engstrom, A Ilyas, S Santurkar, D Tsipras, F Janoos, L Rudolph, ...
International conference on learning representations, 2019
631*2019
Training GANs with Optimism
C Daskalakis, A Ilyas, V Syrgkanis, H Zeng
arXiv preprint arXiv:1711.00141, 2017
6042017
Do adversarially robust imagenet models transfer better?
H Salman, A Ilyas, L Engstrom, A Kapoor, A Madry
Advances in Neural Information Processing Systems 33, 2020
4842020
Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors
A Ilyas, L Engstrom, A Madry
arXiv preprint arXiv:1807.07978, 2018
4552018
Noise or Signal: The Role of Image Backgrounds in Object Recognition
K Xiao, L Engstrom, A Ilyas, A Madry
arXiv preprint arXiv:2006.09994, 2020
4182020
Learning perceptually-aligned representations via adversarial robustness
L Engstrom, A Ilyas, S Santurkar, D Tsipras, B Tran, A Madry
arXiv preprint arXiv:1906.00945 2 (3), 5, 2019
270*2019
Robustness (python library), 2019
L Engstrom, A Ilyas, S Santurkar, D Tsipras
URL https://github. com/MadryLab/robustness, 0
240*
Image synthesis with a single (robust) classifier
S Santurkar, A Ilyas, D Tsipras, L Engstrom, B Tran, A Madry
Advances in Neural Information Processing Systems 32, 2019
238*2019
The robust manifold defense: Adversarial training using generative models
A Ilyas, A Jalal, E Asteri, C Daskalakis, AG Dimakis
arXiv preprint arXiv:1712.09196, 2017
2052017
Datamodels: Predicting Predictions from Training Data
A Ilyas, SM Park, L Engstrom, G Leclerc, A Madry
arXiv preprint arXiv:2202.00622, 2022
180*2022
From imagenet to image classification: Contextualizing progress on benchmarks
D Tsipras, S Santurkar, L Engstrom, A Ilyas, A Madry
International Conference on Machine Learning, 9625-9635, 2020
1742020
A Closer Look at Deep Policy Gradients
A Ilyas, L Engstrom, S Santurkar, D Tsipras, F Janoos, L Rudolph, ...
arXiv preprint arXiv:1811.02553, 2018
165*2018
Evaluating and Understanding the Robustness of Adversarial Logit Pairing
L Engstrom, A Ilyas, A Athalye
arXiv preprint arXiv:1807.10272, 2018
1532018
TRAK: Attributing Model Behavior at Scale
SM Park, K Georgiev, A Ilyas, G Leclerc, A Madry
arXiv preprint arXiv:2303.14186, 2023
1272023
Raising the Cost of Malicious AI-Powered Image Editing
H Salman, A Khaddaj, G Leclerc, A Ilyas, A Madry
arXiv preprint arXiv:2302.06588, 2023
1072023
ffcv
G Leclerc, A Ilyas, L Engstrom, SM Park, H Salman, A Madry
https://github.com/libffcv/ffcv, 2022
85*2022
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Artiklar 1–20