Tao Lin
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    • Learning to Play Multi-Follower Bayesian Stackelberg Games
    • A Unified Approach to Submodular Maximization Under Noise
    • Generalized Principal-Agent Problem with a Learning Agent
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    • Learning Thresholds with Latent Values and Censored Feedback
    • Sample Complexity of Forecast Aggregation
    • From Monopoly to Competition: Optimal Contests Prevail
    • Nash Convergence of Mean-Based Learning Algorithms in First Price Auctions
    • How Many Representatives Do We Need? The Optimal Size of a Congress Voting on Binary Issues
    • Learning Utilities and Equilibria in Non-Truthful Auctions
    • A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling
    • Private Data Manipulation in Optimal Sponsored Search Auction
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    • Information Design with Large Language Models
    • Learning to Coordinate Bidders in Non-Truthful Auctions
    • How to Avoid Polarization in Recommender Systems with Dual Influence?
    • Bayesian Persuasion with a Learning Agent
    • Generalized Principal-Agent Problem with a Learning Agent
    • Private Data Manipulation in Sponsored Search Auctions
    • Sample Complexity of Forecast Aggregation
    • Persuading a Behavioral Agent: Approximately Best Responding and Learning
    • Nash Convergence of Mean-Based Learning Algorithms in First Price Auctions
    • Robustness of Empirical Revenue Maximization in Auction Learning
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    • Information Design with Large Language Models: An Annotated Reading List
    • Generalized Principal-Agent Problem with a Learning Agent
    • From Monopoly to Competition: When Do Optimal Contests Prevail?
    • Private Data Manipulation in Sponsored Search Auctions
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    • On Clearing Prices in Matching Markets: A Simple Characterization without Duality
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Learning a Game by Paying the Agents

Apr 24, 2026·
Brian Hu Zhang*
,
Tao Lin*
,
Yiling Chen
,
Tuomas Sandholm
· 0 min read
PDF URL
Last updated on Apr 24, 2026
Revealed Preference Online Learning Multi-Agent Learning
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