Tao Lin
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    • 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
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    • 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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    • On Clearing Prices in Matching Markets: A Simple Characterization without Duality
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Bias Detection via Signaling

Dec 1, 2024·
(Alphabetical) Yiling Chen
,
Tao Lin
,
Ariel D. Procaccia
,
Aaditya Ramdas
,
Itai Shapira
· 0 min read
PDF Cite URL
Type
Conference paper
Publication
Advances in Neural Information Processing Systems (NeurIPS)
Last updated on Dec 1, 2024
← User-Creator Feature Polarization in Recommender Systems with Dual Influence Dec 10, 2024
Multi-Sender Persuasion: A Computational Perspective Jul 1, 2024 →

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