Aleksander Madry
44 papers · 2018–2025 · 5 venues · across top CS/AI venues
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Research topics
Machine Learning
(38)
Artificial Intelligence
(23)
Core AI
(22)
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(19)
Optimization & Theory
(19)
Learning Types Β· Machine Learning
(18)
Deep Learning
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Computer Vision
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Reinforcement Learning
(2)
Keywords
adversarial robustness
(9)
image classification
(6)
adversarial perturbation
(4)
neural network
(4)
adversarial learning
(4)
benchmark evaluation
(4)
feature representation
(4)
domain generalization
(3)
model debugging
(3)
adversarial example
(3)
data attribution
(3)
spurious correlation
(3)
data poisoning
(2)
robust optimization
(2)
feature attribution
(2)
policy gradient
(2)
robust classification
(2)
object recognition
(2)
computer vision
(2)
deep reinforcement learning
(2)
Papers
Machine Unlearning via Simulated Oracle Matching
ICLR 2025
MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering
ICLR 2025
Small-to-Large Generalization: Training Data Influences Models Consistently Across Scale
ICLR 2025
ContextCite: Attributing Model Generation to Context
NeurIPS 2024
Decomposing and Editing Predictions by Modeling Model Computation
ICML 2024
DsDm: Model-Aware Dataset Selection with Datamodels
ICML 2024
Improving Subgroup Robustness via Data Selection
NeurIPS 2024
A Data-Based Perspective on Transfer Learning
CVPR 2023
Distilling Model Failures as Directions in Latent Space
ICLR 2023
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
Adversarially trained neural representations may already be as robust as corresponding biological neural representations
ICML 2022
Certified Patch Robustness via Smoothed Vision Transformers
CVPR 2022
Combining Diverse Feature Priors
ICML 2022
Datamodels: Understanding Predictions with Data and Data with Predictions
ICML 2022
Missingness Bias in Model Debugging
ICLR 2022
BREEDS: Benchmarks for Subpopulation Shift
ICLR 2021
Editing a classifier by rewriting its prediction rules
NeurIPS 2021
Leveraging Sparse Linear Layers for Debuggable Deep Networks
ICML 2021
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
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
On Adaptive Attacks to Adversarial Example Defenses
NeurIPS 2020
Adversarial Examples Are Not Bugs, They Are Features
NeurIPS 2019
Exploring the Landscape of Spatial Robustness
ICML 2019
Image Synthesis with a Single (Robust) Classifier
NeurIPS 2019
Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors
ICLR 2019
Robustness May Be at Odds with Accuracy
ICLR 2019
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability
ICLR 2019
A Classification-Based Study of Covariate Shift in GAN Distributions
ICML 2018
Adversarially Robust Generalization Requires More Data
NeurIPS 2018
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians
AISTATS 2018
How Does Batch Normalization Help Optimization?
NeurIPS 2018
On the Limitations of First-Order Approximation in GAN Dynamics
ICML 2018
Spectral Signatures in Backdoor Attacks
NeurIPS 2018
Towards Deep Learning Models Resistant to Adversarial Attacks
ICLR 2018