Publications and Preprints
[Economics and Machine Learning]
[Statistical Learning in Dynamical Systems]
Preprints
(Note: students under my supervision; * corresponding author)
-
Incentive-aware recommender systems in two-sided markets. [pdf]
Xiaowu Dai, Yuan Qi, and Michael Jordan.
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+.
Yuantong Li, Guang Cheng, and Xiaowu Dai*.
Preprint, 2023+.
-
Another look at statistical calibration: A non-asymptotic theory and prediction-oriented optimality. [pdf]
Xiaowu Dai and Peter Chien.
Preprint, 2023+.
-
Selection and estimation optimality in high dimensions with the TWIN penalty. [pdf]
Xiaowu Dai and Jared Huling.
Preprint, 2023+.
Xiaowu Dai* and Hengzhi He.
Preprint, 2023+; Under Revisions at Journal of the American Statistical Association: Theory and Methods.
-
Post-regularization confidence bands for ordinary differential equations. [pdf]
Xiaowu Dai and Lexin Li.
Preprint, 2023+; Under Revisions at Journal of Machine Learning Research.
-
Nonparametric estimation via mixed gradients. [pdf]
Xiaowu Dai.
Preprint, 2023+; Under Revisions at Journal of the Royal Statistical Society: Series B.
Publications
(Note: students under my supervision; * corresponding author)
-
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.
-
A resampling approach for causal inference on novel two-point time-series with application to identify risk factors for type-2 diabetes and cardiovascular disease. [preprint][code]
Xiaowu Dai*, Saad Mouti, Marjorie Lima do Vale, Sumantra Ray, Jeffrey Bohn, and Lisa Goldberg.
Statistics in Biosciences (SIBS), 2023.
Xiaowu Dai and Lexin Li.
Journal of the American Statistical Association: Theory and Methods (JASA), 2022.
Xiaowu Dai and Lexin Li.
Journal of the American Statistical Association: Theory and Methods (JASA), 2022.
-
Learning in multi-stage decentralized matching markets. [proceedings][preprint]
Xiaowu Dai and Michael Jordan.
Advances in Neural Information Processing Systems (NeurIPS), 2021.
Xiaowu Dai, Xiang Lyu, and Lexin Li.
Journal of the American Statistical Association: Theory and Methods (JASA), 2021.
-
Learning strategies in decentralized matching markets under uncertain preferences. [journal][preprint]
Xiaowu Dai and Michael Jordan.
Journal of Machine Learning Research (JMLR), 2021.
-
A synthesis of pathways linking diet, metabolic risk and cardiovascular disease: A framework to guide further research and approaches to evidence-based practice. [journal][pubmed]
Marjorie Lima do Vale, Luke Buckner, Claudia-Gabriela Mitrofan, Kai Sento Kargbo, Rajna Golubic, Ali Ahsan Khalid, Sammyia Ashraf, Saad Mouti, Xiaowu Dai, David Unwin, Jeffrey Bohn, Lisa Goldberg, and Sumantra Ray.
Nutrition Research Reviews (NRR), 2021.
-
On large batch training and sharp minima: A Fokker-Planck perspective. [journal][preprint][older version]
Xiaowu Dai and Yuhua Zhu.
Journal of Statistical Theory and Practice (JSTP), special issue on "Advances in Deep Learning", 2020.
-
High-dimensional smoothing splines and application in Alzheimer's disease prediction using magnetic resonance imaging. [journal][preprint]
Xiaowu Dai.
Statistics in Biopharmaceutical Research (SBR), 2020.
-
High-dimensional varying coefficient models for Alzheimer's disease diagnosis with longitudinal and heterogeneous structural MR images. [journal]
Xiaowu Dai.
Alzheimer's & Dementia (AD), 2018.
Miscellaneous
-
Statistical learning-aided design for a blockchain payment system. [pdf]
Xiaowu Dai.
Research Vignette, Simons Institute for the Theory of Computing, 2020.
-
Statistical machine learning for complex data sets. [pdf]
Xiaowu Dai.
Ph.D. Thesis, Department of Statistics, UW-Madison, 2019.