Tao Lin
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    • A Unified Approach to Submodular Maximization Under Noise
    • Generalized Principal-Agent Problem with a Learning Agent
    • Information Design with Unknown Prior
    • User-Creator Feature Polarization in Recommender Systems with Dual Influence
    • Bias Detection via Signaling
    • Multi-Sender Persuasion: A Computational Perspective
    • 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
  • Recent & Upcoming Talks
    • 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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    • Generalized Principal-Agent Problem with a Learning Agent
    • From Monopoly to Competition: When Do Optimal Contests Prevail?
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    • Learning to Play Multi-Follower Bayesian Stackelberg Games
    • WOMAC: A Mechanism For Prediction Competitions
    • Explainable Information Design
    • Learning to Coordinate Bidders in Non-Truthful Auctions
    • Learning a Game by Paying the Agents
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    • How Does Independence Help Generalization? Sample Complexity of ERM on Product Distributions
    • On Clearing Prices in Matching Markets: A Simple Characterization without Duality
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Explainable Information Design

Aug 19, 2025·
(Alphabet) Yiling Chen
,
Tao Lin
,
Wei Tang
,
Jamie Tucker-Foltz
· 0 min read
PDF Cite
Last updated on Aug 19, 2025
Information Design Approximation Algorithm Explainability
← WOMAC: A Mechanism For Prediction Competitions Aug 25, 2025
Learning to Coordinate Bidders in Non-Truthful Auctions Jul 4, 2025 →

© 2025. This work is licensed under CC BY NC ND 4.0

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