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Dimitris Tsipras
Dimitris Tsipras
Verified email at stanford.edu - Homepage
Title
Cited by
Cited by
Year
Towards Deep Learning Models Resistant to Adversarial Attacks
A Madry, A Makelov, L Schmidt, D Tsipras, A Vladu
International Conference on Learning Representations (ICLR), 2018
113042018
How Does Batch Normalization Help Optimization?
S Santurkar, D Tsipras, A Ilyas, A Madry
Neural Information Processing Systems (NeurIPS), 2018
19882018
Adversarial examples are not bugs, they are features
A Ilyas, S Santurkar, D Tsipras, L Engstrom, B Tran, A Madry
Neural Information Processing Systems (NeurIPS), 2019
18522019
Robustness may be at odds with accuracy
D Tsipras, S Santurkar, L Engstrom, A Turner, A Madry
International Conference on Learning Representations (ICLR), 2019
18162019
On Evaluating Adversarial Robustness
N Carlini, A Athalye, N Papernot, W Brendel, J Rauber, D Tsipras, ...
arXiv preprint arXiv:1902.06705, 2019
9232019
Exploring the Landscape of Spatial Robustness
L Engstrom, B Tran, D Tsipras, L Schmidt, A Madry
International Conference on Machine Learning (ICML), 2019
840*2019
Adversarially robust generalization requires more data
L Schmidt, S Santurkar, D Tsipras, K Talwar, A Madry
Neural Information Processing Systems (NeurIPS), 2018
8032018
Holistic Evaluation of Language Models
P Liang, R Bommasani, T Lee, D Tsipras, D Soylu, M Yasunaga, Y Zhang, ...
arXiv preprint arXiv:2211.09110, 2022
5672022
Label-Consistent Backdoor Attacks
A Turner, D Tsipras, A Madry
arXiv preprint arXiv:1912.02771, 2019
448*2019
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 (ICLR), 2019
415*2019
Dataset security for machine learning: Data poisoning, backdoor attacks, and defenses
M Goldblum, D Tsipras, C Xie, X Chen, A Schwarzschild, D Song, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
252*2022
Adversarial robustness as a prior for learned representations
L Engstrom, A Ilyas, S Santurkar, D Tsipras, B Tran, A Madry
arXiv preprint arXiv:1906.00945, 2019
239*2019
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes
S Garg, D Tsipras, P Liang, G Valiant
Neural Information Processing Systems (NeurIPS), 2022
2202022
Image Synthesis with a Single (Robust) Classifier
S Santurkar, A Ilyas, D Tsipras, L Engstrom, B Tran, A Madry
Neural Information Processing Systems (NeurIPS), 2019
210*2019
Robustness (python library), 2019
L Engstrom, A Ilyas, S Santurkar, D Tsipras
https://github. com/MadryLab/robustness, 0
197*
BREEDS: Benchmarks for Subpopulation Shift
S Santurkar, D Tsipras, A Madry
International Conference on Learning Representations (ICLR), 2021
1502021
From imagenet to image classification: Contextualizing progress on benchmarks
D Tsipras, S Santurkar, L Engstrom, A Ilyas, A Madry
International Conference on Machine Learning (ICML), 2020
1432020
A Closer Look at Deep Policy Gradients
A Ilyas, L Engstrom, S Santurkar, D Tsipras, F Janoos, L Rudolph, ...
International Conference on Learning Representations (ICLR), 2020
131*2020
Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods
MB Cohen, A Madry, D Tsipras, A Vladu
Foundations of Computer Science (FOCS), 2017
1252017
Editing a classifier by rewriting its prediction rules
S Santurkar, D Tsipras, M Elango, D Bau, A Torralba, A Madry
Neural Information Processing Systems (NeurIPS), 2021
592021
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Articles 1–20