Dimitris Tsipras

According to our database, Dimitris Tsipras authored at least 29 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Holistic Evaluation of Language Models.

Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

Trans. Mach. Learn. Res., 2023

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses.

Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein

IEEE Trans. Pattern Anal. Mach. Intell., 2023

2022

What Can Transformers Learn In-Context? A Case Study of Simple Function Classes.

Shivam Garg, Dimitris Tsipras, Percy Liang, Gregory Valiant

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Combining Diverse Feature Priors.

Saachi Jain, Dimitris Tsipras, Aleksander Madry

Proceedings of the International Conference on Machine Learning, 2022

2021

Learning Through the Lens of Robustness.

Dimitris Tsipras

PhD thesis, 2021

Editing a classifier by rewriting its prediction rules.

Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

BREEDS: Benchmarks for Subpopulation Shift.

Shibani Santurkar, Dimitris Tsipras, Aleksander Madry

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO.

Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

CoRR, 2020

From ImageNet to Image Classification: Contextualizing Progress on Benchmarks.

Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry

Proceedings of the 37th International Conference on Machine Learning, 2020

Identifying Statistical Bias in Dataset Replication.

Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry

Proceedings of the 37th International Conference on Machine Learning, 2020

A Closer Look at Deep Policy Gradients.

Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

Proceedings of the 8th International Conference on Learning Representations, 2020

Implementation Matters in Deep RL: A Case Study on PPO and TRPO.

Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Label-Consistent Backdoor Attacks.

Alexander Turner, Dimitris Tsipras, Aleksander Madry

CoRR, 2019

Computer Vision with a Single (Robust) Classifier.

Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Andrew Ilyas, Logan Engstrom, Aleksander Madry

CoRR, 2019

Learning Perceptually-Aligned Representations via Adversarial Robustness.

Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Aleksander Madry

CoRR, 2019

On Evaluating Adversarial Robustness.

Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian J. Goodfellow, Aleksander Madry, Alexey Kurakin

CoRR, 2019

Image Synthesis with a Single (Robust) Classifier.

Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Adversarial Examples Are Not Bugs, They Are Features.

Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Exploring the Landscape of Spatial Robustness.

Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry

Proceedings of the 36th International Conference on Machine Learning, 2019

Robustness May Be at Odds with Accuracy.

Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms?

Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

CoRR, 2018

There Is No Free Lunch In Adversarial Robustness (But There Are Unexpected Benefits).

Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry

CoRR, 2018

How Does Batch Normalization Help Optimization? (No, It Is Not About Internal Covariate Shift).

Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry

CoRR, 2018

Adversarially Robust Generalization Requires More Data.

Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

How Does Batch Normalization Help Optimization?

Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Towards Deep Learning Models Resistant to Adversarial Attacks.

Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations.

Logan Engstrom, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry

CoRR, 2017

Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods.

Michael B. Cohen, Aleksander Madry, Dimitris Tsipras, Adrian Vladu

Proceedings of the 58th IEEE Annual Symposium on Foundations of Computer Science, 2017

2016

Efficient Money Burning in General Domains.

Dimitris Fotakis, Dimitris Tsipras, Christos Tzamos, Emmanouil Zampetakis

Theory Comput. Syst., 2016