​​

Economics and Machine Learning​

[Matching markets, Mechanism design, Theory of 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.

​

• Learning in multi-stage decentralized matching markets. [proceedings][preprint]

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. [journal][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 designing real-world matching systems, such as Hilbert Matching [App Store], a matching system for the clothing industry.