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Tao Lin
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Year
Nash convergence of mean-based learning algorithms in first price auctions
X Deng, X Hu, T Lin, W Zheng
Proceedings of the ACM Web Conference 2022, 141-150, 2022
112022
Learning utilities and equilibria in non-truthful auctions
H Fu, T Lin
Advances in Neural Information Processing Systems 33, 14231-14242, 2020
112020
Private data manipulation in optimal sponsored search auction
X Deng, T Lin, T Xiao
Proceedings of The Web Conference 2020, 2676-2682, 2020
52020
Persuading a behavioral agent: Approximately best responding and learning
Y Chen, T Lin
arXiv preprint arXiv:2302.03719, 2023
42023
The Optimal Size of an Epistemic Congress
M Revel, T Lin, D Halpern
arXiv preprint arXiv:2107.01042, 2021
42021
A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling
X Deng, R Lavi, T Lin, Q Qi, W Wang, X Yan
Advances in Neural Information Processing Systems 33, 5215-5226, 2020
42020
From monopoly to competition: optimal contests prevail
X Deng, Y Gafni, R Lavi, T Lin, H Ling
Proceedings of the AAAI Conference on Artificial Intelligence 37 (5), 5608-5615, 2023
32023
How Many Representatives Do We Need? The Optimal Size of a Congress Voting on Binary Issues
M Revel, T Lin, D Halpern
Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 9431-9438, 2022
22022
Persuading a Learning Agent
T Lin, Y Chen
arXiv preprint arXiv:2402.09721, 2024
12024
Sample Complexity of Forecast Aggregation
T Lin, Y Chen
Advances in Neural Information Processing Systems 36, 2024
2024
Learning Thresholds with Latent Values and Censored Feedback
J Zhang, T Lin, W Zheng, Z Feng, Y Teng, X Deng
arXiv preprint arXiv:2312.04653, 2023
2023
How Does Independence Help Generalization? Sample Complexity of ERM on Product Distributions
T Lin
arXiv preprint arXiv:2212.06422, 2022
2022
On Clearing Prices in Matching Markets: A Simple Characterization without Duality
X Li, T Lin
arXiv preprint arXiv:1912.00786, 2019
2019
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Articles 1–13