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Michael Kearns

29 papers · 2006–2026 · 7 venues · across top CS/AI venues

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Achievements

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+11 more ↓ πŸ—ΊοΈ Taxonomy Completionist (50) πŸƒ Academic Marathon Β· Ultra 🌍 Conference Polyglot Β· Silver πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
🌱 Topic Pioneer 🌟 Keyword Trendsetter Combo (7) 🀝 Dynamic Duo (16) πŸ† Keyword Champion 🧭 Keyword Pioneer πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (156) πŸ”₯ Unstoppable Β· Bronze πŸ’Ž Century Club Β· Bronze 🌈 Renaissance Researcher (7)

Venues

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

Top co-authors

Aaron Roth (16) Jessica Sorrell (4) Zhiwei Steven Wu (4) Kareem Amin (3) Shahin Jabbari (3) Jennifer Wortman (3) Sikata Bela Sengupta (3) Jamie Morgenstern (3) Marcel Hussing (3) Shuai Tang (2)

Research topics

Machine Learning (26) Optimization & Theory (19) Application Areas (13) Artificial Intelligence (12) Mathematics & Optimization (9) Core AI (8) Core Methods (7) Optimization (7) Learning Types (4) Reinforcement Learning (3) Bayesian & Probabilistic Β· Artificial Intelligence (3) Bayesian & Probabilistic Β· Machine Learning (3) Mathematics (3) Methods (3) Computer Science (2)

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

Model Agreement via Anchoring COLT 2026 Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces ICML 2025 Membership Inference Attacks on Diffusion Models via Quantile Regression ICML 2024 Oracle-Efficient Reinforcement Learning for Max Value Ensembles NeurIPS 2024 Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable NeurIPS 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 NeurIPS 2019 Differentially Private Fair Learning ICML 2019 Equilibrium Characterization for Data Acquisition Games IJCAI 2019 Network Formation under Random Attack and Probabilistic Spread IJCAI 2019 Online Learning with an Unknown Fairness Metric NeurIPS 2018 Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness ICML 2018 Fairness in Reinforcement Learning ICML 2017 Meritocratic Fairness for Cross-Population Selection ICML 2017 Predicting with Distributions COLT 2017 Fairness in Learning: Classic and Contextual Bandits NeurIPS 2016 Tight Policy Regret Bounds for Improving and Decaying Bandits IJCAI 2016 Efficient Inference for Complex Queries on Complex Distributions AISTATS 2014 Learning from Contagion (Without Timestamps) ICML 2014 Pursuit-Evasion Without Regret, with an Application to Trading ICML 2014 Large-Scale Bandit Problems and KWIK Learning ICML 2013 Marginals-to-Models Reducibility NeurIPS 2013 Bandits, Query Learning, and the Haystack Dimension COLT 2011 Learning from Multiple Sources JMLR 2008 Privacy-Preserving Belief Propagation and Sampling NeurIPS 2007 A Small World Threshold for Economic Network Formation NeurIPS 2006 Learning from Multiple Sources NeurIPS 2006