Madry, Aleksander

57 publications

TMLR 2025 Ask Your Distribution Shift if Pre-Training Is Right for You Benjamin Cohen-Wang, Joshua Vendrow, Aleksander Madry

ICLR 2025 MLE-Bench: Evaluating Machine Learning Agents on Machine Learning Engineering Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, James Aung, Dane Sherburn, Evan Mays, Giulio Starace, Kevin Liu, Leon Maksin, Tejal Patwardhan, Aleksander Madry, Lilian Weng

ICLR 2025 Machine Unlearning via Simulated Oracle Matching Kristian Georgiev, Roy Rinberg, Sung Min Park, Shivam Garg, Andrew Ilyas, Aleksander Madry, Seth Neel

ICLR 2025 Small-to-Large Generalization: Training Data Influences Models Consistently Across Scale Alaa Khaddaj, Logan Engstrom, Aleksander Madry

NeurIPS 2024 ContextCite: Attributing Model Generation to Context Benjamin Cohen-Wang, Harshay Shah, Kristian Georgiev, Aleksander Mądry

ICMLW 2024 ContextCite: Attributing Model Generation to Context Benjamin Cohen-Wang, Harshay Shah, Kristian Georgiev, Aleksander Madry

ICMLW 2024 ContextCite: Attributing Model Generation to Context Benjamin Cohen-Wang, Harshay Shah, Kristian Georgiev, Aleksander Madry

ICML 2024 Decomposing and Editing Predictions by Modeling Model Computation Harshay Shah, Andrew Ilyas, Aleksander Madry

ICMLW 2024 Decomposing and Editing Predictions by Modeling Model Computation Harshay Shah, Andrew Ilyas, Aleksander Madry

NeurIPSW 2024 Decomposing and Editing Predictions by Modeling Model Computation Harshay Shah, Andrew Ilyas, Aleksander Madry

ICML 2024 DsDm: Model-Aware Dataset Selection with Datamodels Logan Engstrom, Axel Feldmann, Aleksander Madry

NeurIPS 2024 Improving Subgroup Robustness via Data Selection Saachi Jain, Kimia Hamidieh, Kristian Georgiev, Andrew Ilyas, Marzyeh Ghassemi, Aleksander Mądry

NeurIPSW 2024 Large Language Model Benchmarks Do Not Test Reliability Joshua Vendrow, Edward Vendrow, Sara Beery, Aleksander Madry

CVPR 2023 A Data-Based Perspective on Transfer Learning Saachi Jain, Hadi Salman, Alaa Khaddaj, Eric Wong, Sung Min Park, Aleksander Mądry

NeurIPSW 2023 Ask Your Distribution Shift if Pre-Training Is Right for You Benjamin Cohen-Wang, Joshua Vendrow, Aleksander Madry

NeurIPSW 2023 Better than Balancing: Debiasing Through Data Attribution Saachi Jain, Kimia Hamidieh, Kristian Georgiev, Marzyeh Ghassemi, Aleksander Madry

ICLR 2023 Distilling Model Failures as Directions in Latent Space Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry

NeurIPSW 2023 Extra Training Provides a Strong Baseline for CLIP Alaa Khaddaj, Hadi Salman, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry

CVPR 2023 FFCV: Accelerating Training by Removing Data Bottlenecks Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Mądry

ICML 2023 ModelDiff: A Framework for Comparing Learning Algorithms Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry

ICML 2023 Raising the Cost of Malicious AI-Powered Image Editing Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry

ICML 2023 Rethinking Backdoor Attacks Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry

ICML 2023 TRAK: Attributing Model Behavior at Scale Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry

ICMLW 2023 The Journey, Not the Destination: How Data Guides Diffusion Models Kristian Georgiev, Joshua Vendrow, Hadi Salman, Sung Min Park, Aleksander Madry

ICMLW 2023 What Works in Chest X-Ray Classification? a Case Study of Design Choices Evan Vogelbaum, Logan Engstrom, Aleksander Madry

NeurIPS 2022 3DB: A Framework for Debugging Computer Vision Models Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry

NeurIPSW 2022 A Unified Framework for Comparing Learning Algorithms Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry

ICML 2022 Adversarially Trained Neural Representations May Already Be as Robust as Corresponding Biological Neural Representations Chong Guo, Michael Lee, Guillaume Leclerc, Joel Dapello, Yug Rao, Aleksander Madry, James Dicarlo

CVPR 2022 Certified Patch Robustness via Smoothed Vision Transformers Hadi Salman, Saachi Jain, Eric Wong, Aleksander Madry

ICML 2022 Combining Diverse Feature Priors Saachi Jain, Dimitris Tsipras, Aleksander Madry

ICML 2022 Datamodels: Understanding Predictions with Data and Data with Predictions Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry

ICLR 2022 Missingness Bias in Model Debugging Saachi Jain, Hadi Salman, Eric Wong, Pengchuan Zhang, Vibhav Vineet, Sai Vemprala, Aleksander Madry

ICLR 2021 BREEDS: Benchmarks for Subpopulation Shift Shibani Santurkar, Dimitris Tsipras, Aleksander Madry

NeurIPS 2021 Editing a Classifier by Rewriting Its Prediction Rules Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry

ICML 2021 Leveraging Sparse Linear Layers for Debuggable Deep Networks Eric Wong, Shibani Santurkar, Aleksander Madry

ICLR 2021 Noise or Signal: The Role of Image Backgrounds in Object Recognition Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry

NeurIPS 2021 Unadversarial Examples: Designing Objects for Robust Vision Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor

ICLR 2020 A Closer Look at Deep Policy Gradients Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

NeurIPS 2020 Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry

ICML 2020 From ImageNet to Image Classification: Contextualizing Progress on Benchmarks Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry

ICML 2020 Identifying Statistical Bias in Dataset Replication Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry

ICLR 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

NeurIPS 2020 On Adaptive Attacks to Adversarial Example Defenses Florian Tramer, Nicholas Carlini, Wieland Brendel, Aleksander Madry

Distill 2019 A Discussion of 'Adversarial Examples Are Not Bugs, They Are Features' Logan Engstrom, Justin Gilmer, Gabriel Goh, Dan Hendrycks, Andrew Ilyas, Aleksander Madry, Reiichiro Nakano, Preetum Nakkiran, Shibani Santurkar, Brandon Tran, Dimitris Tsipras, Eric Wallace

NeurIPS 2019 Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry

ICML 2019 Exploring the Landscape of Spatial Robustness Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry

NeurIPS 2019 Image Synthesis with a Single (Robust) Classifier Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry

ICLR 2019 Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors Andrew Ilyas, Logan Engstrom, Aleksander Madry

ICLR 2019 Robustness May Be at Odds with Accuracy Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry

ICLR 2019 Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability Kai Y. Xiao, Vincent Tjeng, Nur Muhammad Shafiullah, Aleksander Madry

ICML 2018 A Classification-Based Study of Covariate Shift in GAN Distributions Shibani Santurkar, Ludwig Schmidt, Aleksander Madry

AISTATS 2018 A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians Aleksander Madry, Slobodan Mitrovic, Ludwig Schmidt

NeurIPS 2018 Adversarially Robust Generalization Requires More Data Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry

NeurIPS 2018 How Does Batch Normalization Help Optimization? Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry

ICML 2018 On the Limitations of First-Order Approximation in GAN Dynamics Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt

NeurIPS 2018 Spectral Signatures in Backdoor Attacks Brandon Tran, Jerry Li, Aleksander Madry

ICLR 2018 Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu