Andrew Ilyas
25 papers · 2018–2025 · 5 venues · across top CS/AI venues
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(21)
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(2)
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Century Club Β· Bronze
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Research topics
Machine Learning
(22)
Artificial Intelligence
(13)
Core AI
(12)
Optimization & Theory
(11)
Deep Learning
(10)
Learning Types Β· Machine Learning
(10)
Core Methods
(9)
Application Areas
(8)
Computer Vision
(4)
Learning Types Β· Deep Learning
(3)
Models
(3)
Reinforcement Learning
(2)
Analysis
(2)
Generation
(2)
Methods
(2)
Keywords
image classification
(4)
adversarial robustness
(3)
adversarial example
(3)
computer vision
(2)
influence function
(2)
adversarial learning
(2)
data attribution
(2)
feature representation
(2)
neural network
(2)
benchmark evaluation
(2)
adversarial attack
(2)
deep reinforcement learning
(2)
object recognition
(2)
policy gradient
(2)
logistic regression
(1)
feature learning
(1)
transfer learning
(1)
robust statistics
(1)
data poisoning
(1)
robust classification
(1)
Papers
Machine Unlearning via Simulated Oracle Matching
ICLR 2025
Decomposing and Editing Predictions by Modeling Model Computation
ICML 2024
Improving Subgroup Robustness via Data Selection
NeurIPS 2024
FFCV: Accelerating Training by Removing Data Bottlenecks
CVPR 2023
ModelDiff: A Framework for Comparing Learning Algorithms
ICML 2023
Raising the Cost of Malicious AI-Powered Image Editing
ICML 2023
Rethinking Backdoor Attacks
ICML 2023
TRAK: Attributing Model Behavior at Scale
ICML 2023
3DB: A Framework for Debugging Computer Vision Models
NeurIPS 2022
Datamodels: Understanding Predictions with Data and Data with Predictions
ICML 2022
Noise or Signal: The Role of Image Backgrounds in Object Recognition
ICLR 2021
Unadversarial Examples: Designing Objects for Robust Vision
NeurIPS 2021
A Closer Look at Deep Policy Gradients
ICLR 2020
A Theoretical and Practical Framework for Regression and Classification from Truncated Samples
AISTATS 2020
Do Adversarially Robust ImageNet Models Transfer Better?
NeurIPS 2020
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks
ICML 2020
Identifying Statistical Bias in Dataset Replication
ICML 2020
Implementation Matters in Deep RL: A Case Study on PPO and TRPO
ICLR 2020
Adversarial Examples Are Not Bugs, They Are Features
NeurIPS 2019
Image Synthesis with a Single (Robust) Classifier
NeurIPS 2019
Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors
ICLR 2019
Black-box Adversarial Attacks with Limited Queries and Information
ICML 2018
How Does Batch Normalization Help Optimization?
NeurIPS 2018
Synthesizing Robust Adversarial Examples
ICML 2018
Training GANs with Optimism
ICLR 2018