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.
-
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. [preprint][code]
Jiayi Li, Yuantong Li, and Xiaowu Dai*.
Journal of the Royal Statistical Society: Series B (JRSSB), 2023.
Xiaowu Dai and Hengzhi He.
Preprint, 2023+; Under Revisions at Journal of the American Statistical Association: Theory and Methods.
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.