← Authors

Aaron Roth

49 papers · 2014–2025 · 9 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (9) 🌈 Renaissance Researcher (8) 🐝 Cross-Pollinator (4) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (11) πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (3) 🀝 Dynamic Duo (15) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (16) πŸ† Keyword Champion (2) πŸ’Ž Century Club (49) πŸ—ƒοΈ Keyword Collector (144) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (12) ⚑ Prolific Year (8)

Conferences

ICML (19) NIPS (17) COLT (4) ICLR (4) AISTATS (1) ALT (1) CVPR (1) EMNLP (1) IJCAI (1)

Top co-authors

Michael Kearns (15) Seth Neel (6) Georgy Noarov (6) Zhiwei Steven Wu (6) Steven Z. Wu (5) Christopher Jung (5) Ramya Ramalingam (4) Bo Waggoner (4) Shuai Tang (4) Sergul Aydore (4)

Research topics

Differential Privacy (3) Privacy (3) Statistics (1)

Keywords

differential privacy (12) online learning (5) contextual bandit (5) regret bound (4) fairness constraint (4) data deletion (3) empirical risk minimization (3) machine unlearning (3) membership inference (2) adversarial setting (2) individual fairness (2) false positive rate (2) privacy attack (2) agnostic learning (2) algorithmic fairness (2) statistical query (2) fair classification (2) quantile regression (2) model security (2) linear regression (2)

Papers

Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents ICML 2025
Stronger Neyman Regret Guarantees for Adaptive Experimental Design ICML 2025
The Relationship Between No-Regret Learning and Online Conformal Prediction ICML 2025
Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces ICML 2025
Sample Efficient Omniprediction and Downstream Swap Regret for Non-Linear Losses COLT 2025
Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation ICLR 2025
Conformal Language Model Reasoning with Coherent Factuality ICLR 2025
High-Dimensional Prediction for Sequential Decision Making ICML 2025
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable NIPS 2024
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks ICML 2024
Membership Inference Attacks on Diffusion Models via Quantile Regression ICML 2024
Multicalibration for Confidence Scoring in LLMs ICML 2024
Oracle Efficient Algorithms for Groupwise Regret ICLR 2024
Order of Magnitude Speedups for LLM Membership Inference EMNLP 2024
Conference on Learning Theory 2024: Preface COLT 2024
Oracle-Efficient Reinforcement Learning for Max Value Ensembles NIPS 2024
Batch Multivalid Conformal Prediction ICLR 2023
The Statistical Scope of Multicalibration ICML 2023
Scalable Membership Inference Attacks via Quantile Regression NIPS 2023
Multicalibration as Boosting for Regression ICML 2023
Individually Fair Learning with One-Sided Feedback ICML 2023
Practical Adversarial Multivalid Conformal Prediction NIPS 2022
Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications NIPS 2022
Mixed Differential Privacy in Computer Vision CVPR 2022
Private Synthetic Data for Multitask Learning and Marginal Queries NIPS 2022
Differentially Private Query Release Through Adaptive Projection ICML 2021
Adaptive Machine Unlearning NIPS 2021
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning ALT 2021
Moment Multicalibration for Uncertainty Estimation COLT 2021
Oracle Efficient Private Non-Convex Optimization ICML 2020
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis AISTATS 2020
Differentially Private Fair Learning ICML 2019
Average Individual Fairness: Algorithms, Generalization and Experiments NIPS 2019
Equal Opportunity in Online Classification with Partial Feedback NIPS 2019
Local Differential Privacy for Evolving Data NIPS 2018
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem NIPS 2018
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness ICML 2018
Mitigating Bias in Adaptive Data Gathering via Differential Privacy ICML 2018
Online Learning with an Unknown Fairness Metric NIPS 2018
Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM NIPS 2017
Meritocratic Fairness for Cross-Population Selection ICML 2017
Fairness in Reinforcement Learning ICML 2017
Tight Policy Regret Bounds for Improving and Decaying Bandits IJCAI 2016
Adaptive Learning with Robust Generalization Guarantees COLT 2016
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs NIPS 2016
Privacy Odometers and Filters: Pay-as-you-Go Composition NIPS 2016
Fairness in Learning: Classic and Contextual Bandits NIPS 2016
Generalization in Adaptive Data Analysis and Holdout Reuse NIPS 2015
Dual Query: Practical Private Query Release for High Dimensional Data ICML 2014