Aleksander Madry

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 112

Top Venues

CoRR

ICML

NeurIPS

ICLR

Massachusetts Institute of Technology, Cambridge, MA, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, MA, USA

PHD

Publications

Harshay Shah, Andrew Ilyas, Aleksander Madry
Decomposing and Editing Predictions by Modeling Model Computation. CoRR (2024)
Saachi Jain, Kimia Hamidieh, Kristian Georgiev, Andrew Ilyas, Marzyeh Ghassemi, Aleksander Madry
Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection. CoRR (2024)
Sarah H. Cen, Andrew Ilyas, Jennifer Allen, Hannah Li, Aleksander Madry
Measuring Strategization in Recommendation: Users Adapt Their Behavior to Shape Future Content. CoRR (2024)
Benjamin Cohen-Wang, Joshua Vendrow, Aleksander Madry
Ask Your Distribution Shift if Pre-Training is Right for You. CoRR (2024)
Logan Engstrom, Axel Feldmann, Aleksander Madry
DsDm: Model-Aware Dataset Selection with Datamodels. CoRR (2024)
Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry
Distilling Model Failures as Directions in Latent Space. ICLR (2023)
Kristian Georgiev, Joshua Vendrow, Hadi Salman, Sung Min Park, Aleksander Madry
The Journey, Not the Destination: How Data Guides Diffusion Models. CoRR (2023)
Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry
TRAK: Attributing Model Behavior at Scale. CoRR (2023)
Sarah H. Cen, Aleksander Madry, Devavrat Shah
A User-Driven Framework for Regulating and Auditing Social Media. CoRR (2023)
Saachi Jain, Hadi Salman, Alaa Khaddaj, Eric Wong, Sung Min Park, Aleksander Madry
A Data-Based Perspective on Transfer Learning. CVPR (2023)
Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry
Rethinking Backdoor Attacks. CoRR (2023)
Sarah H. Cen, Andrew Ilyas, Aleksander Madry
User Strategization and Trustworthy Algorithms. CoRR (2023)
Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry
Raising the Cost of Malicious AI-Powered Image Editing. ICML (2023)
Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry
Rethinking Backdoor Attacks. ICML (2023)
Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry
FFCV: Accelerating Training by Removing Data Bottlenecks. CVPR (2023)
Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry
ModelDiff: A Framework for Comparing Learning Algorithms. ICML (2023)
Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry
Raising the Cost of Malicious AI-Powered Image Editing. CoRR (2023)
Joshua Vendrow, Saachi Jain, Logan Engstrom, Aleksander Madry
Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation. CoRR (2023)
Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry
TRAK: Attributing Model Behavior at Scale. ICML (2023)
Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses. IEEE Trans. Pattern Anal. Mach. Intell. 45 (2) (2023)
Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry
FFCV: Accelerating Training by Removing Data Bottlenecks. CoRR (2023)
Chong Guo, Michael J. Lee, Guillaume Leclerc, Joel Dapello, Yug Rao, Aleksander Madry, James J. DiCarlo
Adversarially trained neural representations are already as robust as biological neural representations. ICML (2022)
Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry
Datamodels: Understanding Predictions with Data and Data with Predictions. ICML (2022)
Kyriakos Axiotis, Aleksander Madry, Adrian Vladu
Faster Sparse Minimum Cost Flow by Electrical Flow Localization. FOCS (2022)
Saachi Jain, Hadi Salman, Eric Wong, Pengchuan Zhang, Vibhav Vineet, Sai Vemprala, Aleksander Madry
Missingness Bias in Model Debugging. ICLR (2022)
Saachi Jain, Dimitris Tsipras, Aleksander Madry
Combining Diverse Feature Priors. ICML (2022)
Hadi Salman, Saachi Jain, Eric Wong, Aleksander Madry
Certified Patch Robustness via Smoothed Vision Transformers. CVPR (2022)
Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry
3DB: A Framework for Debugging Computer Vision Models. NeurIPS (2022)
Saachi Jain, Hadi Salman, Eric Wong, Pengchuan Zhang, Vibhav Vineet, Sai Vemprala, Aleksander Madry
Missingness Bias in Model Debugging. CoRR (2022)
Saachi Jain, Hadi Salman, Alaa Khaddaj, Eric Wong, Sung Min Park, Aleksander Madry
A Data-Based Perspective on Transfer Learning. CoRR (2022)
Hadi Salman, Saachi Jain, Andrew Ilyas, Logan Engstrom, Eric Wong, Aleksander Madry
When does Bias Transfer in Transfer Learning? CoRR (2022)
Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry
ModelDiff: A Framework for Comparing Learning Algorithms. CoRR (2022)
Chong Guo, Michael J. Lee, Guillaume Leclerc, Joel Dapello, Yug Rao, Aleksander Madry, James J. DiCarlo
Adversarially trained neural representations may already be as robust as corresponding biological neural representations. CoRR (2022)
Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry
Distilling Model Failures as Directions in Latent Space. CoRR (2022)
Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry
Datamodels: Predicting Predictions from Training Data. CoRR (2022)
Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry
Editing a classifier by rewriting its prediction rules. CoRR (2021)
Eric Wong, Shibani Santurkar, Aleksander Madry
Leveraging Sparse Linear Layers for Debuggable Deep Networks. ICML (2021)
Saachi Jain, Dimitris Tsipras, Aleksander Madry
Combining Diverse Feature Priors. CoRR (2021)
Kyriakos Axiotis, Aleksander Madry, Adrian Vladu
Faster Sparse Minimum Cost Flow by Electrical Flow Localization. FOCS (2021)
Sung Min Park, Kuo-An Wei, Kai Yuanqing Xiao, Jerry Li, Aleksander Madry
On Distinctive Properties of Universal Perturbations. CoRR (2021)
Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor
Unadversarial Examples: Designing Objects for Robust Vision. NeurIPS (2021)
Kyriakos Axiotis, Aleksander Madry, Adrian Vladu
Faster Sparse Minimum Cost Flow by Electrical Flow Localization. CoRR (2021)
Eric Wong, Shibani Santurkar, Aleksander Madry
Leveraging Sparse Linear Layers for Debuggable Deep Networks. CoRR (2021)
Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry
3DB: A Framework for Debugging Computer Vision Models. CoRR (2021)
Shibani Santurkar, Dimitris Tsipras, Aleksander Madry
BREEDS: Benchmarks for Subpopulation Shift. ICLR (2021)
Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry
Editing a classifier by rewriting its prediction rules. NeurIPS (2021)
Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry
Noise or Signal: The Role of Image Backgrounds in Object Recognition. ICLR (2021)
Hadi Salman, Saachi Jain, Eric Wong, Aleksander Madry
Certified Patch Robustness via Smoothed Vision Transformers. CoRR (2021)
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. CoRR (2020)
Kyriakos Axiotis, Aleksander Madry, Adrian Vladu
Circulation Control for Faster Minimum Cost Flow in Unit-Capacity Graphs. CoRR (2020)
Florian Tramèr, Nicholas Carlini, Wieland Brendel, Aleksander Madry
On Adaptive Attacks to Adversarial Example Defenses. NeurIPS (2020)
Florian Tramèr, Nicholas Carlini, Wieland Brendel, Aleksander Madry
On Adaptive Attacks to Adversarial Example Defenses. CoRR (2020)
Artur Czumaj, Jakub Lacki, Aleksander Madry, Slobodan Mitrovic, Krzysztof Onak, Piotr Sankowski
Round Compression for Parallel Matching Algorithms. SIAM J. Comput. 49 (5) (2020)
Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry
Do Adversarially Robust ImageNet Models Transfer Better? CoRR (2020)
Shibani Santurkar, Dimitris Tsipras, Aleksander Madry
BREEDS: Benchmarks for Subpopulation Shift. CoRR (2020)
Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry
Do Adversarially Robust ImageNet Models Transfer Better? NeurIPS (2020)
Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry
Noise or Signal: The Role of Image Backgrounds in Object Recognition. CoRR (2020)
Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry
Implementation Matters in Deep RL: A Case Study on PPO and TRPO. ICLR (2020)
Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry
Identifying Statistical Bias in Dataset Replication. ICML (2020)
Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry
A Closer Look at Deep Policy Gradients. ICLR (2020)
Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry
Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO. CoRR (2020)
Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry
Identifying Statistical Bias in Dataset Replication. CoRR (2020)
Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses. CoRR (2020)
Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor
Unadversarial Examples: Designing Objects for Robust Vision. CoRR (2020)
Guillaume Leclerc, Aleksander Madry
The Two Regimes of Deep Network Training. CoRR (2020)
Kyriakos Axiotis, Aleksander Madry, Adrian Vladu
Circulation Control for Faster Minimum Cost Flow in Unit-Capacity Graphs. FOCS (2020)
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. ICML (2020)
Alexander Turner, Dimitris Tsipras, Aleksander Madry
Label-Consistent Backdoor Attacks. CoRR (2019)
Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Aleksander Madry
Learning Perceptually-Aligned Representations via Adversarial Robustness. CoRR (2019)
Kai Yuanqing Xiao, Vincent Tjeng, Nur Muhammad (Mahi) Shafiullah, Aleksander Madry
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability. ICLR (Poster) (2019)
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry
Adversarial Examples Are Not Bugs, They Are Features. NeurIPS (2019)
Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry
Exploring the Landscape of Spatial Robustness. ICML (2019)
Andrew Ilyas, Logan Engstrom, Aleksander Madry
Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors. ICLR (Poster) (2019)
Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry
Image Synthesis with a Single (Robust) Classifier. NeurIPS (2019)
Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian J. Goodfellow, Aleksander Madry, Alexey Kurakin
On Evaluating Adversarial Robustness. CoRR (2019)
Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Andrew Ilyas, Logan Engstrom, Aleksander Madry
Computer Vision with a Single (Robust) Classifier. CoRR (2019)
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry
Adversarial Examples Are Not Bugs, They Are Features. CoRR (2019)
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry
Robustness May Be at Odds with Accuracy. ICLR (Poster) (2019)
Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry
How Does Batch Normalization Help Optimization? NeurIPS (2018)
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry
Adversarially Robust Generalization Requires More Data. NeurIPS (2018)
Kai Yuanqing Xiao, Vincent Tjeng, Nur Muhammad (Mahi) Shafiullah, Aleksander Madry
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability. CoRR (2018)
Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt
On the Limitations of First-Order Approximation in GAN Dynamics. ICML (2018)
Aleksander Madry, Slobodan Mitrovic, Ludwig Schmidt
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians. AISTATS (2018)
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu
Towards Deep Learning Models Resistant to Adversarial Attacks. ICLR (Poster) (2018)
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry
Adversarially Robust Generalization Requires More Data. CoRR (2018)
Brandon Tran, Jerry Li, Aleksander Madry
Spectral Signatures in Backdoor Attacks. CoRR (2018)
Andrew Ilyas, Logan Engstrom, Aleksander Madry
Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors. CoRR (2018)
Shibani Santurkar, Ludwig Schmidt, Aleksander Madry
A Classification-Based Study of Covariate Shift in GAN Distributions. ICML (2018)
Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry
How Does Batch Normalization Help Optimization? (No, It Is Not About Internal Covariate Shift). CoRR (2018)
Artur Czumaj, Jakub Lacki, Aleksander Madry, Slobodan Mitrovic, Krzysztof Onak, Piotr Sankowski
Round compression for parallel matching algorithms. STOC (2018)
Sébastien Bubeck, Michael B. Cohen, Yin Tat Lee, James R. Lee, Aleksander Madry
k-server via multiscale entropic regularization. STOC (2018)
Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry
Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms? CoRR (2018)
Brandon Tran, Jerry Li, Aleksander Madry
Spectral Signatures in Backdoor Attacks. NeurIPS (2018)
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry
There Is No Free Lunch In Adversarial Robustness (But There Are Unexpected Benefits). CoRR (2018)
Michael B. Cohen, Aleksander Madry, Piotr Sankowski, Adrian Vladu
) Time (Extended Abstract). SODA (2017)
Sébastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee, Aleksander Madry
k-server via multiscale entropic regularization. CoRR (2017)
Marco Chiesa, Ilya Nikolaevskiy, Slobodan Mitrovic, Andrei V. Gurtov, Aleksander Madry, Michael Schapira, Scott Shenker
On the Resiliency of Static Forwarding Tables. IEEE/ACM Trans. Netw. 25 (2) (2017)
Shibani Santurkar, Ludwig Schmidt, Aleksander Madry
A Classification-Based Perspective on GAN Distributions. CoRR (2017)
Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt
Towards Understanding the Dynamics of Generative Adversarial Networks. CoRR (2017)
Michael B. Cohen, Aleksander Madry, Dimitris Tsipras, Adrian Vladu
Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods. CoRR (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Aleksander Madry