Andrew Ilyas
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
21
Venues
7
Active years
2018–2025
Best venue rank
A*
Where they publish
Papers
21 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AIES | AI Supply Chains: An Emerging Ecosystem of AI Actors, Products, and Services. | Aspen K. Hopkins, Sarah H. Cen, Isabella Struckman, Andrew Ilyas, Luis Videgaray, Aleksander Madry |
| 2025 | ICLR | Machine Unlearning via Simulated Oracle Matching. | Kristian Georgiev, Roy Rinberg, Sung Min Park, Shivam Garg, Andrew Ilyas, Aleksander Madry, Seth Neel |
| 2024 | ICML | Decomposing and Editing Predictions by Modeling Model Computation. | Harshay Shah, Andrew Ilyas, Aleksander Madry |
| 2023 | CVPR | FFCV: Accelerating Training by Removing Data Bottlenecks. | Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry |
| 2023 | ICML | Rethinking Backdoor Attacks. | Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry |
| 2023 | ICML | TRAK: Attributing Model Behavior at Scale. | Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry |
| 2023 | ICML | Raising the Cost of Malicious AI-Powered Image Editing. | Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry |
| 2023 | ICML | ModelDiff: A Framework for Comparing Learning Algorithms. | Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry |
| 2023 | STOC | What Makes a Good Fisherman? Linear Regression under Self-Selection Bias. | Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis |
| 2022 | ICML | Datamodels: Understanding Predictions with Data and Data with Predictions. | Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry |
| 2021 | ICLR | Noise or Signal: The Role of Image Backgrounds in Object Recognition. | Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry |
| 2020 | AISTATS | A Theoretical and Practical Framework for Regression and Classification from Truncated Samples. | Andrew Ilyas, Emmanouil Zampetakis, Constantinos Daskalakis |
| 2020 | ICLR | 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 |
| 2020 | ICLR | A Closer Look at Deep Policy Gradients. | Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry |
| 2020 | ICML | Identifying Statistical Bias in Dataset Replication. | Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry |
| 2020 | ICML | From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. | Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry |
| 2019 | ICLR | Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors. | Andrew Ilyas, Logan Engstrom, Aleksander Madry |
| 2018 | ICDE | Extracting Syntactical Patterns from Databases. | Andrew Ilyas, Joana M. F. da Trindade, Raul Castro Fernandez, Samuel Madden |
| 2018 | ICLR | Training GANs with Optimism. | Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng |
| 2018 | ICML | Synthesizing Robust Adversarial Examples. | Anish Athalye, Logan Engstrom, Andrew Ilyas, Kevin Kwok |
| 2018 | ICML | Black-box Adversarial Attacks with Limited Queries and Information. | Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin |