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Economics and Machine Learning

[Matching markets, Mechanism design, Incentives]

(Note:     student author;  * corresponding author.)

  • Learning strategies in decentralized matching markets under uncertain preferences. [journal][preprint]

Xiaowu Dai and Michael Jordan. 

Journal of Machine Learning Research (JMLR), 2021.

Xiaowu Dai and Michael Jordan. 

Advances in Neural Information Processing Systems (NeurIPS), 2021.

  • Discussion: "Estimating means of bounded random variables by betting" by Waudby-Smith and Ramdas. [preprint][code]

Jiayi Li, Yuantong Li, and Xiaowu Dai*.

Journal of the Royal Statistical Society: Series B (JRSSB), 2023.

  • An ODE model for dynamic matching in heterogeneous networks. [pdf][code]

Xiaowu Dai and Hengzhi He.

Preprint, 2023+; Under Revisions at Journal of the American Statistical Association: Theory and Methods.

  • Double matching under complementary preferences. [pdf][code​]

Yuantong Li, Guang Cheng, and Xiaowu Dai*. 

Preprint, 2023+.

  • Robust multi-item auction design using statistical learning: Overcoming uncertainty in bidders' types distributions. [pdf][code]

Jiale Han and Xiaowu Dai*. 

Preprint, 2023+.

  • Incentive-aware recommender systems in two-sided markets. [pdf​]

Xiaowu Dai, Yuan Qi, and Michael Jordan.

Preprint, 2023+.

I'm also interested in building real-world matching systems: Hilbert Matching [App Store], a matching system for clothing businesses. 

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