← Authors

Michael Kearns

28 papers · 2006–2025 · 7 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (14) πŸƒ Academic Marathon (19) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) πŸ—ΊοΈ Taxonomy Completionist (21) 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (6) 🀝 Dynamic Duo (15) πŸ† Keyword Champion 🌱 Topic Pioneer πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (62) πŸ”₯ Unstoppable (5) πŸš€ Conference Pioneer πŸ’Ž Century Club (28)

Conferences

ICML (11) NIPS (9) IJCAI (3) COLT (2) AISTATS (1) CVPR (1) JMLR (1)

Top co-authors

Aaron Roth (15) Zhiwei Steven Wu (4) Jamie Morgenstern (3) Jennifer Wortman (3) Jessica Sorrell (3) Shahin Jabbari (3) Kareem Amin (3) Shuai Tang (2) Matthew Joseph (2) Marcel Hussing (2)

Research topics

Privacy (1)

Keywords

regret bound (3) differential privacy (3) online learning (3) fairness constraint (3) graphical model (3) multi-armed bandit (3) algorithmic fairness (2) transfer learning (2) nash equilibrium (2) multi-source learning (2) probabilistic inference (2) domain adaptation (2) agnostic learning (2) expected loss (2) game theory (2) network formation (2) contextual bandit (2) convex optimization (1) classification (1) few-shot learning (1)

Papers

Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces ICML 2025
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable NIPS 2024
Membership Inference Attacks on Diffusion Models via Quantile Regression ICML 2024
Oracle-Efficient Reinforcement Learning for Max Value Ensembles NIPS 2024
Multicalibration as Boosting for Regression ICML 2023
Mixed Differential Privacy in Computer Vision CVPR 2022
Differentially Private Query Release Through Adaptive Projection ICML 2021
Average Individual Fairness: Algorithms, Generalization and Experiments NIPS 2019
Differentially Private Fair Learning ICML 2019
Network Formation under Random Attack and Probabilistic Spread IJCAI 2019
Equilibrium Characterization for Data Acquisition Games IJCAI 2019
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness ICML 2018
Online Learning with an Unknown Fairness Metric NIPS 2018
Predicting with Distributions COLT 2017
Fairness in Reinforcement Learning ICML 2017
Meritocratic Fairness for Cross-Population Selection ICML 2017
Tight Policy Regret Bounds for Improving and Decaying Bandits IJCAI 2016
Fairness in Learning: Classic and Contextual Bandits NIPS 2016
Learning from Contagion (Without Timestamps) ICML 2014
Pursuit-Evasion Without Regret, with an Application to Trading ICML 2014
Efficient Inference for Complex Queries on Complex Distributions AISTATS 2014
Marginals-to-Models Reducibility NIPS 2013
Large-Scale Bandit Problems and KWIK Learning ICML 2013
Bandits, Query Learning, and the Haystack Dimension COLT 2011
Learning from Multiple Sources JMLR 2008
Privacy-Preserving Belief Propagation and Sampling NIPS 2007
A Small World Threshold for Economic Network Formation NIPS 2006
Learning from Multiple Sources NIPS 2006