conftrace_

Andrew Ilyas

25 papers · 2018–2025 · 5 conferences · across top CS/AI conferences

Achievements

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+12 more ↓ 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (7)
🌉 Interdisciplinary Bridge 🏃 Academic Marathon (7) 🧭 Keyword Pioneer 🤝 Dynamic Duo (21) 👑 Triple Crown 💎 Century Club (25) 📈 Trend Setter 🔥 Unstoppable (8) 🚀 Conference Pioneer Prolific Year (6) The Questioner (2) 🗃️ Keyword Collector (96)

Conferences

ICML (10) NIPS (7) ICLR (6) AISTATS (1) CVPR (1)

Research topics

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 NIPS 2024 FFCV: Accelerating Training by Removing Data Bottlenecks CVPR 2023 Raising the Cost of Malicious AI-Powered Image Editing ICML 2023 TRAK: Attributing Model Behavior at Scale ICML 2023 Rethinking Backdoor Attacks ICML 2023 ModelDiff: A Framework for Comparing Learning Algorithms ICML 2023 Datamodels: Understanding Predictions with Data and Data with Predictions ICML 2022 3DB: A Framework for Debugging Computer Vision Models NIPS 2022 Unadversarial Examples: Designing Objects for Robust Vision NIPS 2021 Noise or Signal: The Role of Image Backgrounds in Object Recognition ICLR 2021 A Closer Look at Deep Policy Gradients ICLR 2020 Do Adversarially Robust ImageNet Models Transfer Better? NIPS 2020 A Theoretical and Practical Framework for Regression and Classification from Truncated Samples AISTATS 2020 Implementation Matters in Deep RL: A Case Study on PPO and TRPO ICLR 2020 Identifying Statistical Bias in Dataset Replication ICML 2020 From ImageNet to Image Classification: Contextualizing Progress on Benchmarks ICML 2020 Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors ICLR 2019 Image Synthesis with a Single (Robust) Classifier NIPS 2019 Adversarial Examples Are Not Bugs, They Are Features NIPS 2019 Black-box Adversarial Attacks with Limited Queries and Information ICML 2018 Training GANs with Optimism ICLR 2018 Synthesizing Robust Adversarial Examples ICML 2018 How Does Batch Normalization Help Optimization? NIPS 2018