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2020 – today
- 2024
[c27]Harshay Shah, Andrew Ilyas, Aleksander Madry:
Decomposing and Editing Predictions by Modeling Model Computation. ICML 2024- [i34]Harshay Shah, Andrew Ilyas, Aleksander Madry:
Decomposing and Editing Predictions by Modeling Model Computation. CoRR abs/2404.11534 (2024) - [i33]Sarah H. Cen, Andrew Ilyas, Jennifer Allen, Hannah Li, Aleksander Madry:
Measuring Strategization in Recommendation: Users Adapt Their Behavior to Shape Future Content. CoRR abs/2405.05596 (2024) - [i32]Saachi Jain, Kimia Hamidieh, Kristian Georgiev, Andrew Ilyas, Marzyeh Ghassemi, Aleksander Madry:
Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection. CoRR abs/2406.16846 (2024) - [i31]Kristian Georgiev, Roy Rinberg, Sung Min Park, Shivam Garg, Andrew Ilyas, Aleksander Madry, Seth Neel:
Attribute-to-Delete: Machine Unlearning via Datamodel Matching. CoRR abs/2410.23232 (2024) - 2023
- [c26]Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry:
FFCV: Accelerating Training by Removing Data Bottlenecks. CVPR 2023: 12011-12020 - [c25]Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry:
Rethinking Backdoor Attacks. ICML 2023: 16216-16236 - [c24]Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry:
TRAK: Attributing Model Behavior at Scale. ICML 2023: 27074-27113 - [c23]Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry:
Raising the Cost of Malicious AI-Powered Image Editing. ICML 2023: 29894-29918 - [c22]Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry:
ModelDiff: A Framework for Comparing Learning Algorithms. ICML 2023: 30646-30688 - [c21]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis
:
What Makes a Good Fisherman? Linear Regression under Self-Selection Bias. STOC 2023: 1699-1712 - [i30]Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry:
Raising the Cost of Malicious AI-Powered Image Editing. CoRR abs/2302.06588 (2023) - [i29]Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry:
TRAK: Attributing Model Behavior at Scale. CoRR abs/2303.14186 (2023) - [i28]Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry:
FFCV: Accelerating Training by Removing Data Bottlenecks. CoRR abs/2306.12517 (2023) - [i27]Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry:
Rethinking Backdoor Attacks. CoRR abs/2307.10163 (2023) - [i26]Sarah H. Cen, Andrew Ilyas, Aleksander Madry:
User Strategization and Trustworthy Algorithms. CoRR abs/2312.17666 (2023) - 2022
- [c20]Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry:
Datamodels: Understanding Predictions with Data and Data with Predictions. ICML 2022: 9525-9587 - [c19]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 - [c18]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis:
Estimation of Standard Auction Models. EC 2022: 602-603 - [i25]Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry:
Datamodels: Predicting Predictions from Training Data. CoRR abs/2202.00622 (2022) - [i24]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis:
Estimation of Standard Auction Models. CoRR abs/2205.02060 (2022) - [i23]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis:
What Makes A Good Fisherman? Linear Regression under Self-Selection Bias. CoRR abs/2205.03246 (2022) - [i22]Hadi Salman, Saachi Jain, Andrew Ilyas, Logan Engstrom, Eric Wong, Aleksander Madry:
When does Bias Transfer in Transfer Learning? CoRR abs/2207.02842 (2022) - [i21]Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry:
ModelDiff: A Framework for Comparing Learning Algorithms. CoRR abs/2211.12491 (2022) - 2021
- [c17]Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
Noise or Signal: The Role of Image Backgrounds in Object Recognition. ICLR 2021 - [c16]Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor:
Unadversarial Examples: Designing Objects for Robust Vision. NeurIPS 2021: 15270-15284 - [i20]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 abs/2106.03805 (2021) - 2020
- [c15]Andrew Ilyas, Emmanouil Zampetakis, Constantinos Daskalakis:
A Theoretical and Practical Framework for Regression and Classification from Truncated Samples. AISTATS 2020: 4463-4473 - [c14]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 - [c13]Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
A Closer Look at Deep Policy Gradients. ICLR 2020 - [c12]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry:
Identifying Statistical Bias in Dataset Replication. ICML 2020: 2922-2932 - [c11]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. ICML 2020: 9625-9635 - [c10]Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry:
Do Adversarially Robust ImageNet Models Transfer Better? NeurIPS 2020 - [i19]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry:
Identifying Statistical Bias in Dataset Replication. CoRR abs/2005.09619 (2020) - [i18]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. CoRR abs/2005.11295 (2020) - [i17]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 abs/2005.12729 (2020) - [i16]Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
Noise or Signal: The Role of Image Backgrounds in Object Recognition. CoRR abs/2006.09994 (2020) - [i15]Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry:
Do Adversarially Robust ImageNet Models Transfer Better? CoRR abs/2007.08489 (2020) - [i14]Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor:
Unadversarial Examples: Designing Objects for Robust Vision. CoRR abs/2012.12235 (2020)
2010 – 2019
- 2019
- [c9]Andrew Ilyas, Logan Engstrom, Aleksander Madry:
Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors. ICLR (Poster) 2019 - [c8]Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Adversarial Examples Are Not Bugs, They Are Features. NeurIPS 2019: 125-136 - [c7]Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Image Synthesis with a Single (Robust) Classifier. NeurIPS 2019: 1260-1271 - [i13]Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Adversarial Examples Are Not Bugs, They Are Features. CoRR abs/1905.02175 (2019) - [i12]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Aleksander Madry:
Learning Perceptually-Aligned Representations via Adversarial Robustness. CoRR abs/1906.00945 (2019) - [i11]Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Andrew Ilyas, Logan Engstrom, Aleksander Madry:
Computer Vision with a Single (Robust) Classifier. CoRR abs/1906.09453 (2019) - 2018
- [c6]Andrew Ilyas, Joana M. F. da Trindade, Raul Castro Fernandez, Samuel Madden:
Extracting Syntactical Patterns from Databases. ICDE 2018: 41-52 - [c5]Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng:
Training GANs with Optimism. ICLR (Poster) 2018 - [c4]Anish Athalye, Logan Engstrom, Andrew Ilyas, Kevin Kwok:
Synthesizing Robust Adversarial Examples. ICML 2018: 284-293 - [c3]Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin:
Black-box Adversarial Attacks with Limited Queries and Information. ICML 2018: 2142-2151 - [c2]Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry:
How Does Batch Normalization Help Optimization? NeurIPS 2018: 2488-2498 - [i10]Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin:
Black-box Adversarial Attacks with Limited Queries and Information. CoRR abs/1804.08598 (2018) - [i9]Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry:
How Does Batch Normalization Help Optimization? (No, It Is Not About Internal Covariate Shift). CoRR abs/1805.11604 (2018) - [i8]Andrew Ilyas, Logan Engstrom, Aleksander Madry:
Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors. CoRR abs/1807.07978 (2018) - [i7]Logan Engstrom, Andrew Ilyas, Anish Athalye:
Evaluating and Understanding the Robustness of Adversarial Logit Pairing. CoRR abs/1807.10272 (2018) - [i6]Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms? CoRR abs/1811.02553 (2018) - 2017
- [i5]Anish Athalye, Logan Engstrom, Andrew Ilyas, Kevin Kwok:
Synthesizing Robust Adversarial Examples. CoRR abs/1707.07397 (2017) - [i4]Andrew Ilyas, Joana M. F. da Trindade, Raul Castro Fernandez, Samuel Madden:
Extracting Syntactic Patterns from Databases. CoRR abs/1710.11528 (2017) - [i3]Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis, Haoyang Zeng:
Training GANs with Optimism. CoRR abs/1711.00141 (2017) - [i2]Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin:
Query-Efficient Black-box Adversarial Examples. CoRR abs/1712.07113 (2017) - [i1]Andrew Ilyas, Ajil Jalal, Eirini Asteri, Constantinos Daskalakis, Alexandros G. Dimakis:
The Robust Manifold Defense: Adversarial Training using Generative Models. CoRR abs/1712.09196 (2017) - 2014
- [c1]Andrew Ilyas:
MicroFilters: Harnessing twitter for disaster management. GHTC 2014: 417-424
Coauthor Index
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last updated on 2024-12-01 01:11 CET by the dblp team
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