Ilyas, Andrew

30 publications

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

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

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

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

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

AISTATS 2020 A Theoretical and Practical Framework for Regression and Classification from Truncated Samples Andrew Ilyas, Emmanouil Zampetakis, Constantinos Daskalakis

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

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

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

ICML 2018 Black-Box Adversarial Attacks with Limited Queries and Information Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin

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

ICML 2018 Synthesizing Robust Adversarial Examples Anish Athalye, Logan Engstrom, Andrew Ilyas, Kevin Kwok

ICLR 2018 Training GANs with Optimism Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng